morph-locations-final
Allison Davis Connelly
2024-02-24
Data collection
## Using libcurl 8.3.0 with Schannel##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## `geom_smooth()` using formula = 'y ~ x'
Location effects
Will run an ANOVA on the residuals with location and species as fixed effects. This will show me if morphology depends on the species, the location, and if the location and species interact to determine morphology. CANNOT DO WITH COUNT DATA–may have to run a glmer with zero-tuncated negative binomial/quasi-poisson distribution instead (think this will tell me if species, location, and interaction affect the trait…). Will only work with the residuals, because comparing the means of the residuals indicates differences in variation. Would I not just use Levene’s and MWU again but include spp and zone/basin/watershed?
Leaving the anovas for count data in rn until I figure out what to do.
I will first run this using the zones as the location factor. Zones (1-4) represent the latitude range with equivalent sample sizes in each, since the collections were not equally representative of all latitudes, and I wanted to avoid a sampling bias when randomly selecting samples. Zone 1 corresponds to the southern most latitude range, and zone 4 corresponds to the northern most latitude range.
I will then run the same analysis using basin as the location factor. Since fish are physically isolated to the river basins they occupy, the genetic variation is also limited to that basin. Thus it is possible for fish within the same basin to be more similar due to genetic/physical constraints. (will also do with watershed just to see).
Lastly I will run ANOVAs with both zones and basins but with standardized residuals. This would allow me to compare overall variation across traits (at least those that are depended on body size) rather than just one trait at a time. Not 100% sure if this is useful (or correct to do), but thought it would be interesting.
All data
ANOVAs
Amazon
Zones
library(ggplot2)
lat3 <- raw2[raw2$SPP == "p.latipinna", ]
form3 <- raw2[raw2$SPP == "p.latipinna", ]
A.D.F <- aov(abs.res.D ~ QUARTILE, data=form3)
summary(A.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.306 0.7685 4.292 0.00635 **
## Residuals 130 23.277 0.1791
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.D)) +
geom_boxplot()
A.P1.F <- aov(abs.res.P1 ~ QUARTILE, data=form3)
summary(A.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.159 0.05296 0.444 0.722
## Residuals 130 15.511 0.11932A.P1.R.F <- aov(abs.res.P1.R ~ QUARTILE, data=form3)
summary(A.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.065 0.02172 0.166 0.919
## Residuals 130 16.987 0.13067ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.P1.R)) +
geom_boxplot()
A.LLSC.F <- aov(abs.res.LLSC ~ QUARTILE, data=form3)
summary(A.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.31 0.4354 1.209 0.309
## Residuals 130 46.80 0.3600A.SBLL.F <- aov(abs.res.SBLL ~ QUARTILE, data=form3)
summary(A.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.436 0.1454 1.142 0.335
## Residuals 130 16.546 0.1273ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.SBLL)) +
geom_boxplot()
A.BD.F <- aov(abs.res.BD ~ QUARTILE, data=form3)
summary(A.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00594 0.001981 1.519 0.213
## Residuals 130 0.16955 0.001304ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.BD)) +
geom_boxplot()
A.CPD.F <- aov(abs.res.CPD ~ QUARTILE, data=form3)
summary(A.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01249 0.004163 6.832 0.00026 ***
## Residuals 130 0.07922 0.000609
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.CPD)) +
geom_boxplot()
A.CPL.F <- aov(abs.res.CPL ~ QUARTILE, data=form3)
summary(A.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.02074 0.006912 9.448 1.08e-05 ***
## Residuals 130 0.09511 0.000732
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.CPL)) +
geom_boxplot()
A.PreDL.F <- aov(abs.res.PreDL ~ QUARTILE, data=form3)
summary(A.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00209 0.0006977 1.606 0.191
## Residuals 130 0.05646 0.0004343ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.PreDL)) +
geom_boxplot()
A.DbL.F <- aov(abs.res.DbL ~ QUARTILE, data=form3)
summary(A.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01219 0.004063 2.276 0.0828 .
## Residuals 130 0.23204 0.001785
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.DbL)) +
geom_boxplot()
A.HL.F <- aov(abs.res.HL ~ QUARTILE, data=form3)
summary(A.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00344 0.0011466 1.324 0.269
## Residuals 130 0.11260 0.0008661ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.HL)) +
geom_boxplot()
A.HD.F <- aov(abs.res.HD ~ QUARTILE, data=form3)
summary(A.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00672 0.002239 2.04 0.111
## Residuals 130 0.14269 0.001098A.HW.F <- aov(abs.res.HW ~ QUARTILE, data=form3)
summary(A.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01136 0.003788 7.212 0.000163 ***
## Residuals 130 0.06827 0.000525
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.HW)) +
geom_boxplot()
A.SnL.F <- aov(abs.res.SnL ~ QUARTILE, data=form3)
summary(A.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00766 0.0025545 5.052 0.00242 **
## Residuals 130 0.06573 0.0005056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL.F <- aov(abs.res.OL ~ QUARTILE, data=form3)
summary(A.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.17e-32 7.242e-33 1.538 0.208
## Residuals 130 6.12e-31 4.708e-33ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.OL)) +
geom_boxplot()
Basins
A1.D.F <- aov(abs.res.D ~ BASIN, data=form3)
summary(A1.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 2.789 0.5579 3.133 0.0106 *
## Residuals 128 22.793 0.1781
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.D)) +
geom_boxplot()
A1.P1.F <- aov(abs.res.P1 ~ BASIN, data=form3)
summary(A1.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.945 0.1891 1.643 0.153
## Residuals 128 14.725 0.1150A1.P1.R.F <- aov(abs.res.P1.R ~ BASIN, data=form3)
summary(A1.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.159 0.03187 0.241 0.943
## Residuals 128 16.893 0.13197ggplot(form3, aes(x=factor(BASIN), y=abs.res.P1.R)) +
geom_boxplot()
A1.LLSC.F <- aov(abs.res.LLSC ~ BASIN, data=form3)
summary(A1.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 4.54 0.9080 2.668 0.025 *
## Residuals 128 43.57 0.3404
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.LLSC)) +
geom_boxplot()
A1.SBLL.F <- aov(abs.res.SBLL ~ BASIN, data=form3)
summary(A1.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.755 0.1510 1.191 0.317
## Residuals 128 16.228 0.1268ggplot(form3, aes(x=factor(BASIN), y=abs.res.SBLL)) +
geom_boxplot()
A1.BD.F <- aov(abs.res.BD ~ BASIN, data=form3)
summary(A1.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00786 0.001571 1.2 0.313
## Residuals 128 0.16764 0.001310ggplot(form3, aes(x=factor(BASIN), y=abs.res.BD)) +
geom_boxplot()
A1.CPD.F <- aov(abs.res.CPD ~ BASIN, data=form3)
summary(A1.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01713 0.003425 5.879 6.34e-05 ***
## Residuals 128 0.07458 0.000583
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.CPD)) +
geom_boxplot()
A1.CPL.F <- aov(abs.res.CPL ~ BASIN, data=form3)
summary(A1.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.02013 0.004025 5.383 0.000159 ***
## Residuals 128 0.09572 0.000748
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL.F <- aov(abs.res.PreDL ~ BASIN, data=form3)
summary(A1.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00492 0.0009846 2.35 0.0445 *
## Residuals 128 0.05363 0.0004190
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.PreDL)) +
geom_boxplot()
A1.DbL.F <- aov(abs.res.DbL ~ BASIN, data=form3)
summary(A1.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00996 0.001992 1.088 0.37
## Residuals 128 0.23428 0.001830ggplot(form3, aes(x=factor(BASIN), y=abs.res.DbL)) +
geom_boxplot()
A1.HL.F <- aov(abs.res.HL ~ BASIN, data=form3)
summary(A1.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00766 0.0015321 1.809 0.115
## Residuals 128 0.10838 0.0008467ggplot(form3, aes(x=factor(BASIN), y=abs.res.HL)) +
geom_boxplot()
A1.HD.F <- aov(abs.res.HD ~ BASIN, data=form3)
summary(A1.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00684 0.001367 1.228 0.3
## Residuals 128 0.14257 0.001114ggplot(form3, aes(x=factor(BASIN), y=abs.res.HD)) +
geom_boxplot()
A1.HW.F <- aov(abs.res.HW ~ BASIN, data=form3)
summary(A1.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01460 0.0029194 5.746 8.11e-05 ***
## Residuals 128 0.06504 0.0005081
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.HW)) +
geom_boxplot()
A1.SnL.F <- aov(abs.res.SnL ~ BASIN, data=form3)
summary(A1.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01931 0.003861 9.138 1.87e-07 ***
## Residuals 128 0.05409 0.000423
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL.F <- aov(abs.res.OL ~ BASIN, data=form3)
summary(A1.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 1.240e-32 2.479e-33 0.511 0.768
## Residuals 128 6.214e-31 4.854e-33ggplot(form3, aes(x=factor(BASIN), y=abs.res.OL)) +
geom_boxplot()
Watersheds
A2.D.F <- aov(abs.res.D ~ WATERSHED, data=form3)
summary(A2.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 3.847 0.3497 1.963 0.0378 *
## Residuals 122 21.736 0.1782
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.D)) +
geom_boxplot()
A2.P1.F <- aov(abs.res.P1 ~ WATERSHED, data=form3)
summary(A2.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 1.302 0.1184 1.005 0.446
## Residuals 122 14.368 0.1178A2.P1.R.F <- aov(abs.res.P1.R ~ WATERSHED, data=form3)
summary(A2.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.34 0.03093 0.226 0.995
## Residuals 122 16.71 0.13698ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.P1.R)) +
geom_boxplot()
A2.LLSC.F <- aov(abs.res.LLSC ~ WATERSHED, data=form3)
summary(A2.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 8.16 0.7422 2.267 0.015 *
## Residuals 122 39.94 0.3274
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.LLSC)) +
geom_boxplot()
A2.SBLL.F <- aov(abs.res.SBLL ~ WATERSHED, data=form3)
summary(A2.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 5.086 0.4623 4.741 4.93e-06 ***
## Residuals 122 11.897 0.0975
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.SBLL)) +
geom_boxplot()
A2.BD.F <- aov(abs.res.BD ~ WATERSHED, data=form3)
summary(A2.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01278 0.001162 0.871 0.571
## Residuals 122 0.16271 0.001334ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.BD)) +
geom_boxplot()
A2.CPD.F <- aov(abs.res.CPD ~ WATERSHED, data=form3)
summary(A2.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01833 0.0016662 2.77 0.00304 **
## Residuals 122 0.07338 0.0006015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.CPD)) +
geom_boxplot()
A2.CPL.F <- aov(abs.res.CPL ~ WATERSHED, data=form3)
summary(A2.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.03237 0.0029429 4.301 2.05e-05 ***
## Residuals 122 0.08347 0.0006842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL.F <- aov(abs.res.PreDL ~ WATERSHED, data=form3)
summary(A2.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.00568 0.0005163 1.191 0.3
## Residuals 122 0.05288 0.0004334A2.DbL.F <- aov(abs.res.DbL ~ WATERSHED, data=form3)
summary(A2.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.04272 0.003883 2.351 0.0115 *
## Residuals 122 0.20152 0.001652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.DbL)) +
geom_boxplot()
A2.HL.F <- aov(abs.res.HL ~ WATERSHED, data=form3)
summary(A2.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01169 0.0010627 1.243 0.267
## Residuals 122 0.10435 0.0008553ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HL)) +
geom_boxplot()
A2.HD.F <- aov(abs.res.HD ~ WATERSHED, data=form3)
summary(A2.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01036 0.0009418 0.826 0.614
## Residuals 122 0.13905 0.0011397ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HD)) +
geom_boxplot()
A2.HW.F <- aov(abs.res.HW ~ WATERSHED, data=form3)
summary(A2.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01704 0.0015488 3.018 0.00136 **
## Residuals 122 0.06260 0.0005131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HW)) +
geom_boxplot()
A2.SnL.F <- aov(abs.res.SnL ~ WATERSHED, data=form3)
summary(A2.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.02208 0.0020073 4.772 4.46e-06 ***
## Residuals 122 0.05131 0.0004206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL.F <- aov(abs.res.OL ~ WATERSHED, data=form3)
summary(A2.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.610e-32 2.372e-33 0.476 0.915
## Residuals 122 6.077e-31 4.981e-33ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.OL)) +
geom_boxplot()
Sailfin
Zones
library(ggplot2)
A.D.L <- aov(abs.res.D ~ QUARTILE, data=lat3)
summary(A.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.306 0.7685 4.292 0.00635 **
## Residuals 130 23.277 0.1791
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.D)) +
geom_boxplot()
A.P1.L <- aov(abs.res.P1 ~ QUARTILE, data=lat3)
summary(A.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.159 0.05296 0.444 0.722
## Residuals 130 15.511 0.11932A.P1.R.L <- aov(abs.res.P1.R ~ QUARTILE, data=lat3)
summary(A.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.065 0.02172 0.166 0.919
## Residuals 130 16.987 0.13067ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.P1.R)) +
geom_boxplot()
A.LLSC.L <- aov(abs.res.LLSC ~ QUARTILE, data=lat3)
summary(A.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.31 0.4354 1.209 0.309
## Residuals 130 46.80 0.3600A.SBLL.L <- aov(abs.res.SBLL ~ QUARTILE, data=lat3)
summary(A.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.436 0.1454 1.142 0.335
## Residuals 130 16.546 0.1273ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.SBLL)) +
geom_boxplot()
A.BD.L <- aov(abs.res.BD ~ QUARTILE, data=lat3)
summary(A.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00594 0.001981 1.519 0.213
## Residuals 130 0.16955 0.001304ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.BD)) +
geom_boxplot()
A.CPD.L <- aov(abs.res.CPD ~ QUARTILE, data=lat3)
summary(A.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01249 0.004163 6.832 0.00026 ***
## Residuals 130 0.07922 0.000609
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.CPD)) +
geom_boxplot()
A.CPL.L <- aov(abs.res.CPL ~ QUARTILE, data=lat3)
summary(A.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.02074 0.006912 9.448 1.08e-05 ***
## Residuals 130 0.09511 0.000732
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.CPL)) +
geom_boxplot()
A.PreDL.L <- aov(abs.res.PreDL ~ QUARTILE, data=lat3)
summary(A.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00209 0.0006977 1.606 0.191
## Residuals 130 0.05646 0.0004343ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.PreDL)) +
geom_boxplot()
A.DbL.L <- aov(abs.res.DbL ~ QUARTILE, data=lat3)
summary(A.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01219 0.004063 2.276 0.0828 .
## Residuals 130 0.23204 0.001785
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.DbL)) +
geom_boxplot()
A.HL.L <- aov(abs.res.HL ~ QUARTILE, data=lat3)
summary(A.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00344 0.0011466 1.324 0.269
## Residuals 130 0.11260 0.0008661ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.HL)) +
geom_boxplot()
A.HD.L <- aov(abs.res.HD ~ QUARTILE, data=lat3)
summary(A.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00672 0.002239 2.04 0.111
## Residuals 130 0.14269 0.001098A.HW.L <- aov(abs.res.HW ~ QUARTILE, data=lat3)
summary(A.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01136 0.003788 7.212 0.000163 ***
## Residuals 130 0.06827 0.000525
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.HW)) +
geom_boxplot()
A.SnL.L <- aov(abs.res.SnL ~ QUARTILE, data=lat3)
summary(A.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00766 0.0025545 5.052 0.00242 **
## Residuals 130 0.06573 0.0005056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL.L <- aov(abs.res.OL ~ QUARTILE, data=lat3)
summary(A.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.17e-32 7.242e-33 1.538 0.208
## Residuals 130 6.12e-31 4.708e-33ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.OL)) +
geom_boxplot()
Basins
A1.D.L <- aov(abs.res.D ~ BASIN, data=lat3)
summary(A1.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 2.789 0.5579 3.133 0.0106 *
## Residuals 128 22.793 0.1781
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.D)) +
geom_boxplot()
A1.P1.L <- aov(abs.res.P1 ~ BASIN, data=lat3)
summary(A1.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.945 0.1891 1.643 0.153
## Residuals 128 14.725 0.1150A1.P1.R.L <- aov(abs.res.P1.R ~ BASIN, data=lat3)
summary(A1.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.159 0.03187 0.241 0.943
## Residuals 128 16.893 0.13197ggplot(lat3, aes(x=factor(BASIN), y=abs.res.P1.R)) +
geom_boxplot()
A1.LLSC.L <- aov(abs.res.LLSC ~ BASIN, data=lat3)
summary(A1.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 4.54 0.9080 2.668 0.025 *
## Residuals 128 43.57 0.3404
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.LLSC)) +
geom_boxplot()
A1.SBLL.L <- aov(abs.res.SBLL ~ BASIN, data=lat3)
summary(A1.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.755 0.1510 1.191 0.317
## Residuals 128 16.228 0.1268ggplot(lat3, aes(x=factor(BASIN), y=abs.res.SBLL)) +
geom_boxplot()
A1.BD.L <- aov(abs.res.BD ~ BASIN, data=lat3)
summary(A1.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00786 0.001571 1.2 0.313
## Residuals 128 0.16764 0.001310ggplot(lat3, aes(x=factor(BASIN), y=abs.res.BD)) +
geom_boxplot()
A1.CPD.L <- aov(abs.res.CPD ~ BASIN, data=lat3)
summary(A1.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01713 0.003425 5.879 6.34e-05 ***
## Residuals 128 0.07458 0.000583
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.CPD)) +
geom_boxplot()
A1.CPL.L <- aov(abs.res.CPL ~ BASIN, data=lat3)
summary(A1.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.02013 0.004025 5.383 0.000159 ***
## Residuals 128 0.09572 0.000748
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL.L <- aov(abs.res.PreDL ~ BASIN, data=lat3)
summary(A1.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00492 0.0009846 2.35 0.0445 *
## Residuals 128 0.05363 0.0004190
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.PreDL)) +
geom_boxplot()
A1.DbL.L <- aov(abs.res.DbL ~ BASIN, data=lat3)
summary(A1.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00996 0.001992 1.088 0.37
## Residuals 128 0.23428 0.001830ggplot(lat3, aes(x=factor(BASIN), y=abs.res.DbL)) +
geom_boxplot()
A1.HL.L <- aov(abs.res.HL ~ BASIN, data=lat3)
summary(A1.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00766 0.0015321 1.809 0.115
## Residuals 128 0.10838 0.0008467ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HL)) +
geom_boxplot()
A1.HD.L <- aov(abs.res.HD ~ BASIN, data=lat3)
summary(A1.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00684 0.001367 1.228 0.3
## Residuals 128 0.14257 0.001114ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HD)) +
geom_boxplot()
A1.HW.L <- aov(abs.res.HW ~ BASIN, data=lat3)
summary(A1.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01460 0.0029194 5.746 8.11e-05 ***
## Residuals 128 0.06504 0.0005081
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HW)) +
geom_boxplot()
A1.SnL.L <- aov(abs.res.SnL ~ BASIN, data=lat3)
summary(A1.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01931 0.003861 9.138 1.87e-07 ***
## Residuals 128 0.05409 0.000423
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL.L <- aov(abs.res.OL ~ BASIN, data=lat3)
summary(A1.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 1.240e-32 2.479e-33 0.511 0.768
## Residuals 128 6.214e-31 4.854e-33ggplot(lat3, aes(x=factor(BASIN), y=abs.res.OL)) +
geom_boxplot()
Watersheds
A2.D.L <- aov(abs.res.D ~ WATERSHED, data=lat3)
summary(A2.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 3.847 0.3497 1.963 0.0378 *
## Residuals 122 21.736 0.1782
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.D)) +
geom_boxplot()
A2.P1.L <- aov(abs.res.P1 ~ WATERSHED, data=lat3)
summary(A2.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 1.302 0.1184 1.005 0.446
## Residuals 122 14.368 0.1178A2.P1.R.L <- aov(abs.res.P1.R ~ WATERSHED, data=lat3)
summary(A2.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.34 0.03093 0.226 0.995
## Residuals 122 16.71 0.13698ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.P1.R)) +
geom_boxplot()
A2.LLSC.L <- aov(abs.res.LLSC ~ WATERSHED, data=lat3)
summary(A2.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 8.16 0.7422 2.267 0.015 *
## Residuals 122 39.94 0.3274
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.LLSC)) +
geom_boxplot()
A2.SBLL.L <- aov(abs.res.SBLL ~ WATERSHED, data=lat3)
summary(A2.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 5.086 0.4623 4.741 4.93e-06 ***
## Residuals 122 11.897 0.0975
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.SBLL)) +
geom_boxplot()
A2.BD.L <- aov(abs.res.BD ~ WATERSHED, data=lat3)
summary(A2.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01278 0.001162 0.871 0.571
## Residuals 122 0.16271 0.001334ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.BD)) +
geom_boxplot()
A2.CPD.L <- aov(abs.res.CPD ~ WATERSHED, data=lat3)
summary(A2.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01833 0.0016662 2.77 0.00304 **
## Residuals 122 0.07338 0.0006015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.CPD)) +
geom_boxplot()
A2.CPL.L <- aov(abs.res.CPL ~ WATERSHED, data=lat3)
summary(A2.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.03237 0.0029429 4.301 2.05e-05 ***
## Residuals 122 0.08347 0.0006842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL.L <- aov(abs.res.PreDL ~ WATERSHED, data=lat3)
summary(A2.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.00568 0.0005163 1.191 0.3
## Residuals 122 0.05288 0.0004334A2.DbL.L <- aov(abs.res.DbL ~ WATERSHED, data=lat3)
summary(A2.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.04272 0.003883 2.351 0.0115 *
## Residuals 122 0.20152 0.001652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.DbL)) +
geom_boxplot()
A2.HL.L <- aov(abs.res.HL ~ WATERSHED, data=lat3)
summary(A2.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01169 0.0010627 1.243 0.267
## Residuals 122 0.10435 0.0008553ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HL)) +
geom_boxplot()
A2.HD.L <- aov(abs.res.HD ~ WATERSHED, data=lat3)
summary(A2.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01036 0.0009418 0.826 0.614
## Residuals 122 0.13905 0.0011397ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HD)) +
geom_boxplot()
A2.HW.L <- aov(abs.res.HW ~ WATERSHED, data=lat3)
summary(A2.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01704 0.0015488 3.018 0.00136 **
## Residuals 122 0.06260 0.0005131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HW)) +
geom_boxplot()
A2.SnL.L <- aov(abs.res.SnL ~ WATERSHED, data=lat3)
summary(A2.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.02208 0.0020073 4.772 4.46e-06 ***
## Residuals 122 0.05131 0.0004206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL.L <- aov(abs.res.OL ~ WATERSHED, data=lat3)
summary(A2.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.610e-32 2.372e-33 0.476 0.915
## Residuals 122 6.077e-31 4.981e-33ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.OL)) +
geom_boxplot()
Both
Zones
library(ggplot2)
A.D <- aov(abs.res.D ~ SPP*QUARTILE, data=raw3)
summary(A.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.408 0.52344
## QUARTILE 3 0.45 0.1510 0.970 0.40715
## SPP:QUARTILE 3 3.22 1.0719 6.888 0.00017 ***
## Residuals 292 45.44 0.1556
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A.P1.L <- aov(abs.res.P1 ~ SPP*QUARTILE, data=raw3)
summary(A.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.554 0.214
## QUARTILE 3 1.10 0.3663 1.977 0.117
## SPP:QUARTILE 3 0.73 0.2427 1.310 0.271
## Residuals 292 54.10 0.1853A.P1.R <- aov(abs.res.P1.R ~ SPP*QUARTILE, data=raw3)
summary(A.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.423 0.000824 ***
## QUARTILE 3 0.13 0.0434 0.276 0.842918
## SPP:QUARTILE 3 0.06 0.0189 0.120 0.948162
## Residuals 292 45.97 0.1574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A.LLSC <- aov(abs.res.LLSC ~ SPP*QUARTILE, data=raw3)
summary(A.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 2.940 0.0875 .
## QUARTILE 3 1.35 0.4506 0.945 0.4190
## SPP:QUARTILE 3 3.42 1.1399 2.391 0.0688 .
## Residuals 292 139.19 0.4767
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.SBLL <- aov(abs.res.SBLL ~ SPP*QUARTILE, data=raw3)
summary(A.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 4.859 0.0283 *
## QUARTILE 3 0.78 0.2591 1.930 0.1248
## SPP:QUARTILE 3 0.12 0.0390 0.291 0.8320
## Residuals 292 39.20 0.1342
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A.BD <- aov(abs.res.BD ~ SPP*QUARTILE, data=raw3)
summary(A.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.0000346 0.026 0.8726
## QUARTILE 3 0.0015 0.0004855 0.361 0.7811
## SPP:QUARTILE 3 0.0087 0.0028846 2.146 0.0946 .
## Residuals 292 0.3925 0.0013442
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A.CPD <- aov(abs.res.CPD ~ SPP*QUARTILE, data=raw3)
summary(A.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.900 0.02764 *
## QUARTILE 3 0.00786 0.0026201 4.108 0.00707 **
## SPP:QUARTILE 3 0.00713 0.0023775 3.728 0.01176 *
## Residuals 292 0.18622 0.0006377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A.CPL <- aov(abs.res.CPL ~ SPP*QUARTILE, data=raw3)
summary(A.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.986836
## QUARTILE 3 0.01640 0.005468 6.588 0.000254 ***
## SPP:QUARTILE 3 0.02033 0.006777 8.166 3.08e-05 ***
## Residuals 292 0.24236 0.000830
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.CPL, fill=SPP)) +
geom_boxplot()
A.PreDL <- aov(abs.res.PreDL ~ SPP*QUARTILE, data=raw3)
summary(A.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.145 0.7035
## QUARTILE 3 0.00243 0.0008091 1.991 0.1155
## SPP:QUARTILE 3 0.00392 0.0013082 3.218 0.0232 *
## Residuals 292 0.11869 0.0004065
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.PreDL, fill=SPP)) +
geom_boxplot()
A.DbL <- aov(abs.res.DbL ~ SPP*QUARTILE, data=raw3)
summary(A.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.037 0.847
## QUARTILE 3 0.0060 0.001997 1.093 0.352
## SPP:QUARTILE 3 0.0068 0.002277 1.246 0.293
## Residuals 292 0.5335 0.001827ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A.HL <- aov(abs.res.HL ~ SPP*QUARTILE, data=raw3)
summary(A.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.861 0.3541
## QUARTILE 3 0.02099 0.006995 7.421 8.33e-05 ***
## SPP:QUARTILE 3 0.01029 0.003432 3.640 0.0132 *
## Residuals 292 0.27527 0.000943
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A.HD <- aov(abs.res.HD ~ SPP*QUARTILE, data=raw3)
summary(A.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## QUARTILE 3 0.00443 0.0014757 1.522 0.209
## SPP:QUARTILE 3 0.00582 0.0019390 1.999 0.114
## Residuals 292 0.28319 0.0009698A.HW <- aov(abs.res.HW ~ SPP*QUARTILE, data=raw3)
summary(A.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.861 0.09184 .
## QUARTILE 3 0.00917 0.0030561 4.103 0.00712 **
## SPP:QUARTILE 3 0.00710 0.0023664 3.177 0.02448 *
## Residuals 292 0.21750 0.0007449
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A.SnL <- aov(abs.res.SnL ~ SPP*QUARTILE, data=raw3)
summary(A.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.000095 0.163 0.6867
## QUARTILE 3 0.01743 0.005809 9.995 2.73e-06 ***
## SPP:QUARTILE 3 0.00494 0.001647 2.833 0.0386 *
## Residuals 292 0.16972 0.000581
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL <- aov(abs.res.OL ~ SPP*QUARTILE, data=raw3)
summary(A.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.108 0.1476
## QUARTILE 3 1.830e-32 6.103e-33 2.617 0.0512 .
## SPP:QUARTILE 3 5.800e-33 1.948e-33 0.835 0.4754
## Residuals 292 6.809e-31 2.332e-33
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Basins
A1.D <- aov(abs.res.D ~ SPP*BASIN, data=raw3)
summary(A1.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.402 0.52666
## BASIN 6 3.12 0.5205 3.293 0.00377 **
## SPP:BASIN 3 0.31 0.1028 0.650 0.58344
## Residuals 289 45.68 0.1581
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A1.P1 <- aov(abs.res.P1 ~ SPP*BASIN, data=raw3)
summary(A1.P1)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.528 0.217
## BASIN 6 0.97 0.1613 0.856 0.528
## SPP:BASIN 3 0.53 0.1751 0.930 0.427
## Residuals 289 54.43 0.1883A1.P1.R <- aov(abs.res.P1.R ~ SPP*BASIN, data=raw3)
summary(A1.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.421 0.000826 ***
## BASIN 6 0.51 0.0845 0.537 0.780341
## SPP:BASIN 3 0.15 0.0485 0.308 0.819718
## Residuals 289 45.50 0.1575
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A1.LLSC <- aov(abs.res.LLSC ~ SPP*BASIN, data=raw3)
summary(A1.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 2.999 0.0844 .
## BASIN 6 6.83 1.1376 2.435 0.0260 *
## SPP:BASIN 3 2.11 0.7026 1.504 0.2137
## Residuals 289 135.02 0.4672
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.LLSC, fill=SPP)) +
geom_boxplot()
A1.SBLL <- aov(abs.res.SBLL ~ SPP*BASIN, data=raw3)
summary(A1.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 4.895 0.0277 *
## BASIN 6 1.07 0.1785 1.340 0.2393
## SPP:BASIN 3 0.51 0.1716 1.288 0.2788
## Residuals 289 38.51 0.1332
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A1.BD <- aov(abs.res.BD ~ SPP*BASIN, data=raw3)
summary(A1.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.000035 0.027 0.8701
## BASIN 6 0.0190 0.003167 2.450 0.0251 *
## SPP:BASIN 3 0.0101 0.003367 2.605 0.0520 .
## Residuals 289 0.3735 0.001292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A1.CPD <- aov(abs.res.CPD ~ SPP*BASIN, data=raw3)
summary(A1.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.984 0.026343 *
## BASIN 6 0.01576 0.0026273 4.191 0.000464 ***
## SPP:BASIN 3 0.00428 0.0014261 2.275 0.080070 .
## Residuals 289 0.18117 0.0006269
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A1.CPL <- aov(abs.res.CPL ~ SPP*BASIN, data=raw3)
summary(A1.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.987
## BASIN 6 0.03228 0.005380 6.320 2.92e-06 ***
## SPP:BASIN 3 0.00078 0.000259 0.304 0.822
## Residuals 289 0.24603 0.000851
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL <- aov(abs.res.PreDL ~ SPP*BASIN, data=raw3)
summary(A1.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.147 0.7020
## BASIN 6 0.00466 0.0007773 1.932 0.0755 .
## SPP:BASIN 3 0.00412 0.0013741 3.416 0.0178 *
## Residuals 289 0.11626 0.0004023
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.PreDL, fill=SPP)) +
geom_boxplot()
A1.DbL <- aov(abs.res.DbL ~ SPP*BASIN, data=raw3)
summary(A1.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.037 0.847
## BASIN 6 0.0152 0.002539 1.397 0.216
## SPP:BASIN 3 0.0057 0.001914 1.053 0.370
## Residuals 289 0.5254 0.001818ggplot(raw3, aes(x=factor(BASIN), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A1.HL <- aov(abs.res.HL ~ SPP*BASIN, data=raw3)
summary(A1.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.827 0.36379
## BASIN 6 0.02039 0.003398 3.463 0.00255 **
## SPP:BASIN 3 0.00256 0.000852 0.868 0.45782
## Residuals 289 0.28360 0.000981
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A1.HD <- aov(abs.res.HD ~ SPP*BASIN, data=raw3)
summary(A1.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## BASIN 6 0.00478 0.0007959 0.808 0.565
## SPP:BASIN 3 0.00382 0.0012743 1.293 0.277
## Residuals 289 0.28484 0.0009856ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HD, fill=SPP)) +
geom_boxplot()
A1.HW <- aov(abs.res.HW ~ SPP*BASIN, data=raw3)
summary(A1.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.825 0.09387 .
## BASIN 6 0.01505 0.0025085 3.326 0.00349 **
## SPP:BASIN 3 0.00076 0.0002544 0.337 0.79838
## Residuals 289 0.21795 0.0007542
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A1.SnL <- aov(abs.res.SnL ~ SPP*BASIN, data=raw3)
summary(A1.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.000095 0.162 0.688
## BASIN 6 0.02054 0.003424 5.849 8.99e-06 ***
## SPP:BASIN 3 0.00238 0.000794 1.357 0.256
## Residuals 289 0.16916 0.000585
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL <- aov(abs.res.OL ~ SPP*BASIN, data=raw3)
summary(A1.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.054 0.153
## BASIN 6 9.200e-33 1.535e-33 0.641 0.697
## SPP:BASIN 3 4.100e-33 1.358e-33 0.567 0.637
## Residuals 289 6.917e-31 2.394e-33ggplot(raw3, aes(x=factor(BASIN), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Watersheds
A2.D <- aov(abs.res.D ~ SPP*WATERSHED, data=raw3)
summary(A2.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.415 0.5198
## WATERSHED 13 4.33 0.3331 2.178 0.0106 *
## SPP:WATERSHED 5 1.96 0.3922 2.564 0.0274 *
## Residuals 280 42.82 0.1529
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A2.P1 <- aov(abs.res.P1 ~ SPP*WATERSHED, data=raw3)
summary(A2.P1)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.568 0.2116
## WATERSHED 13 3.73 0.2868 1.562 0.0957 .
## SPP:WATERSHED 5 0.78 0.1569 0.855 0.5120
## Residuals 280 51.41 0.1836
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.P1.R <- aov(abs.res.P1.R ~ SPP*WATERSHED, data=raw3)
summary(A2.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.145 0.000957 ***
## WATERSHED 13 0.82 0.0629 0.390 0.972416
## SPP:WATERSHED 5 0.16 0.0322 0.199 0.962521
## Residuals 280 45.18 0.1614
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A2.LLSC <- aov(abs.res.LLSC ~ SPP*WATERSHED, data=raw3)
summary(A2.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 3.299 0.0704 .
## WATERSHED 13 20.28 1.5596 3.672 2.15e-05 ***
## SPP:WATERSHED 5 4.75 0.9502 2.237 0.0509 .
## Residuals 280 118.93 0.4248
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.LLSC, fill=SPP)) +
geom_boxplot()
A2.SBLL <- aov(abs.res.SBLL ~ SPP*WATERSHED, data=raw3)
summary(A2.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 5.611 0.0185 *
## WATERSHED 13 2.98 0.2289 1.969 0.0233 *
## SPP:WATERSHED 5 4.57 0.9138 7.861 6.06e-07 ***
## Residuals 280 32.55 0.1162
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A2.BD <- aov(abs.res.BD ~ SPP*WATERSHED, data=raw3)
summary(A2.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.000035 0.028 0.86766
## WATERSHED 13 0.0427 0.003283 2.639 0.00171 **
## SPP:WATERSHED 5 0.0115 0.002309 1.856 0.10214
## Residuals 280 0.3484 0.001244
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A2.CPD <- aov(abs.res.CPD ~ SPP*WATERSHED, data=raw3)
summary(A2.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.943 0.0270 *
## WATERSHED 13 0.01690 0.0012999 2.056 0.0169 *
## SPP:WATERSHED 5 0.00731 0.0014624 2.313 0.0441 *
## Residuals 280 0.17700 0.0006322
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A2.CPL <- aov(abs.res.CPL ~ SPP*WATERSHED, data=raw3)
summary(A2.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.9866
## WATERSHED 13 0.04566 0.003512 4.406 8.64e-07 ***
## SPP:WATERSHED 5 0.01021 0.002043 2.563 0.0275 *
## Residuals 280 0.22322 0.000797
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL <- aov(abs.res.PreDL ~ SPP*WATERSHED, data=raw3)
summary(A2.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.146 0.7022
## WATERSHED 13 0.00996 0.0007664 1.902 0.0297 *
## SPP:WATERSHED 5 0.00229 0.0004575 1.136 0.3416
## Residuals 280 0.11279 0.0004028
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.DbL <- aov(abs.res.DbL ~ SPP*WATERSHED, data=raw3)
summary(A2.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.040 0.841516
## WATERSHED 13 0.0348 0.002680 1.579 0.090441 .
## SPP:WATERSHED 5 0.0363 0.007253 4.273 0.000923 ***
## Residuals 280 0.4752 0.001697
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A2.HL <- aov(abs.res.HL ~ SPP*WATERSHED, data=raw3)
summary(A2.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.896 0.345
## WATERSHED 13 0.05036 0.003874 4.275 1.54e-06 ***
## SPP:WATERSHED 5 0.00247 0.000494 0.546 0.742
## Residuals 280 0.25372 0.000906
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A2.HD <- aov(abs.res.HD ~ SPP*WATERSHED, data=raw3)
summary(A2.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## WATERSHED 13 0.01725 0.0013271 1.371 0.173
## SPP:WATERSHED 5 0.00519 0.0010375 1.072 0.376
## Residuals 280 0.27100 0.0009678ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HD, fill=SPP)) +
geom_boxplot()
A2.HW <- aov(abs.res.HW ~ SPP*WATERSHED, data=raw3)
summary(A2.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.862 0.0918 .
## WATERSHED 13 0.02008 0.0015446 2.075 0.0157 *
## SPP:WATERSHED 5 0.00521 0.0010418 1.399 0.2246
## Residuals 280 0.20848 0.0007446
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A2.SnL <- aov(abs.res.SnL ~ SPP*WATERSHED, data=raw3)
summary(A2.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.0000948 0.180 0.672
## WATERSHED 13 0.04027 0.0030976 5.890 1.23e-09 ***
## SPP:WATERSHED 5 0.00457 0.0009144 1.739 0.126
## Residuals 280 0.14725 0.0005259
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL <- aov(abs.res.OL ~ SPP*WATERSHED, data=raw3)
summary(A2.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.037 0.155
## WATERSHED 13 2.900e-32 2.231e-33 0.925 0.528
## SPP:WATERSHED 5 2.000e-34 4.600e-35 0.019 1.000
## Residuals 280 6.758e-31 2.414e-33ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Standardized
DON’T KNOW IF THIS IS USEFUL
The ANOVAs above focus on differences of particular traits as a factor of species and location. If we want to get an idea of variation in general as a factor of species and location, we can standardize the residuals (essentially unitless z-scores of residuals).
sd.res.D <- append(abs(sd.lat.D), abs(sd.form.D))
sd.res.P1 <- append(abs(sd.lat.P1), abs(sd.form.P1))
sd.res.P1.R <- append(abs(sd.lat.P1.R), abs(sd.form.P1.R))
sd.res.LLSC<- append(abs(sd.lat.LLSC), abs(sd.form.LLSC))
sd.res.SBLL<- append(abs(sd.lat.SBLL), abs(sd.form.SBLL))
sd.res.BD<- append(abs(sd.lat.BD), abs(sd.form.BD))
sd.res.CPD<- append(abs(sd.lat.CPD), abs(sd.form.CPD))
sd.res.CPL<- append(abs(sd.lat.CPL), abs(sd.form.CPL))
sd.res.PreDL <- append(abs(sd.lat.PreDL), abs(sd.form.PreDL))
sd.res.DbL <- append(abs(sd.lat.DbL), abs(sd.form.DbL))
sd.res.HL<- append(abs(sd.lat.HL), abs(sd.form.HL))
sd.res.HD<- append(abs(sd.lat.HD), abs(sd.form.HD))
sd.res.HW <- append(abs(sd.lat.HW), abs(sd.form.HW))
sd.res.SnL <- append(abs(sd.lat.SnL), abs(sd.form.SnL))
sd.res.OL <- append(abs(sd.lat.OL), abs(sd.form.OL))
raw4 <- cbind(raw3, sd.res.D, sd.res.P1, sd.res.P1.R, sd.res.LLSC, sd.res.SBLL, sd.res.BD, sd.res.CPD, sd.res.CPL, sd.res.PreDL, sd.res.DbL, sd.res.HL, sd.res.HD, sd.res.HW, sd.res.SnL, sd.res.OL)
raw5 <- cbind(raw4[1:14], stack(raw4[53:68])) ## Warning in data.frame(..., check.names = FALSE): row names were found from a
## short variable and have been discardedlat.raw5 <- raw5[raw5$SPP == "p.latipinna",]
form.raw5 <- raw5[raw5$SPP == "p.formosa",]
######ZONES#####
A3.lat <- aov(values~QUARTILE, data=lat.raw5)
summary(A3.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.6 0.2106 1.13 0.336
## Residuals 2140 398.9 0.1864A3.form <- aov(values~QUARTILE, data=form.raw5)
summary(A3.form)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.9 0.6213 2.851 0.0361 *
## Residuals 2652 578.0 0.2180
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#between species
A3 <- aov(values~QUARTILE*SPP, data=raw5)
summary(A3)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.8 0.2626 1.288 0.277
## SPP 1 0.1 0.0604 0.296 0.586
## QUARTILE:SPP 3 1.7 0.5578 2.736 0.042 *
## Residuals 4792 976.9 0.2039
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw5, aes(x=factor(QUARTILE), y=values, fill=SPP)) +
geom_boxplot()
######BASINS#####
A4.lat <- aov(values~BASIN, data=lat.raw5)
summary(A4.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.8 0.1597 0.856 0.51
## Residuals 2138 398.7 0.1865A4.form <- aov(values~BASIN, data=form.raw5)
summary(A4.form)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 4 0.6 0.1525 0.698 0.593
## Residuals 2651 579.3 0.2185#between species
A4 <- aov(values~BASIN*SPP, data=raw5)
summary(A4)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 6 0.6 0.09760 0.478 0.825
## SPP 1 0.0 0.03245 0.159 0.690
## BASIN:SPP 3 0.8 0.27201 1.332 0.262
## Residuals 4789 978.0 0.20422ggplot(raw5, aes(x=factor(BASIN), y=values, fill=SPP)) +
geom_boxplot()
#####WATERSHEDS#####
A5.lat <- aov(values~WATERSHED, data=lat.raw5)
summary(A5.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.7 0.2441 1.312 0.211
## Residuals 2132 396.8 0.1861A5.form <- aov(values~WATERSHED, data=form.raw5)
summary(A5.form)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 5.9 0.8383 3.867 0.000339 ***
## Residuals 2648 574.0 0.2168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#between species
A5 <- aov(values~WATERSHED*SPP, data=raw5)
summary(A5)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 13 5.9 0.4574 2.252 0.00609 **
## SPP 1 0.2 0.1715 0.844 0.35818
## WATERSHED:SPP 5 2.5 0.4924 2.424 0.03332 *
## Residuals 4780 970.8 0.2031
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw5, aes(x=factor(WATERSHED), y=values, fill=SPP)) +
geom_boxplot()
GLMMs
Will run mixed models with zones/basins/watersheds as random effect. This will account for any variation seen at these levels and show us if there are any consistent species differences. Can only do this with residuals.
Zones
library(lme4)## Loading required package: Matrixlibrary(lmerTest)##
## Attaching package: 'lmerTest'## The following object is masked from 'package:lme4':
##
## lmer## The following object is masked from 'package:stats':
##
## stepMM.D <- glmer(abs.res.D ~ SPP + (1|QUARTILE), data=raw3)#originally had family=poisson, since this is count data, but because this was the residuals of count data, the values were non-integers and poisson only deals with integers. ## Warning in glmer(abs.res.D ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.D.a <- anova(MM.D, test="Chisq")## Warning in anova.merMod(MM.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.06351 Min. :0.06351 Min. :0.3854
## 1st Qu.:1 1st Qu.:0.06351 1st Qu.:0.06351 1st Qu.:0.3854
## Median :1 Median :0.06351 Median :0.06351 Median :0.3854
## Mean :1 Mean :0.06351 Mean :0.06351 Mean :0.3854
## 3rd Qu.:1 3rd Qu.:0.06351 3rd Qu.:0.06351 3rd Qu.:0.3854
## Max. :1 Max. :0.06351 Max. :0.06351 Max. :0.3854MM.P1 <- glmer(abs.res.P1 ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.P1 ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.P1.a <- anova(MM.P1, test="Chisq")## Warning in anova.merMod(MM.P1, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.P1.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.3631 Min. :0.3631 Min. :1.956
## 1st Qu.:1 1st Qu.:0.3631 1st Qu.:0.3631 1st Qu.:1.956
## Median :1 Median :0.3631 Median :0.3631 Median :1.956
## Mean :1 Mean :0.3631 Mean :0.3631 Mean :1.956
## 3rd Qu.:1 3rd Qu.:0.3631 3rd Qu.:0.3631 3rd Qu.:1.956
## Max. :1 Max. :0.3631 Max. :0.3631 Max. :1.956MM.P1.R <- glmer(abs.res.P1.R ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.P1.R ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.P1.Ra <- anova(MM.P1.R, test="Chisq")## Warning in anova.merMod(MM.P1.R, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.798 Min. :1.798 Min. :11.61
## 1st Qu.:1 1st Qu.:1.798 1st Qu.:1.798 1st Qu.:11.61
## Median :1 Median :1.798 Median :1.798 Median :11.61
## Mean :1 Mean :1.798 Mean :1.798 Mean :11.61
## 3rd Qu.:1 3rd Qu.:1.798 3rd Qu.:1.798 3rd Qu.:11.61
## Max. :1 Max. :1.798 Max. :1.798 Max. :11.61MM.LLSC <- glmer(abs.res.LLSC ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.LLSC ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.LLSC.a <- anova(MM.LLSC, test="Chisq")## Warning in anova.merMod(MM.LLSC, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.401 Min. :1.401 Min. :2.901
## 1st Qu.:1 1st Qu.:1.401 1st Qu.:1.401 1st Qu.:2.901
## Median :1 Median :1.401 Median :1.401 Median :2.901
## Mean :1 Mean :1.401 Mean :1.401 Mean :2.901
## 3rd Qu.:1 3rd Qu.:1.401 3rd Qu.:1.401 3rd Qu.:2.901
## Max. :1 Max. :1.401 Max. :1.401 Max. :2.901MM.SBLL <- glmer(abs.res.SBLL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.SBLL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.SBLL.a <- anova(MM.SBLL, test="Chisq")## Warning in anova.merMod(MM.SBLL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.5775 Min. :0.5775 Min. :4.335
## 1st Qu.:1 1st Qu.:0.5775 1st Qu.:0.5775 1st Qu.:4.335
## Median :1 Median :0.5775 Median :0.5775 Median :4.335
## Mean :1 Mean :0.5775 Mean :0.5775 Mean :4.335
## 3rd Qu.:1 3rd Qu.:0.5775 3rd Qu.:0.5775 3rd Qu.:4.335
## Max. :1 Max. :0.5775 Max. :0.5775 Max. :4.335MM.BD <- glmer(abs.res.BD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.BD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.BD.a <- anova(MM.BD, test="Chisq")## Warning in anova.merMod(MM.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.461e-05 Min. :3.461e-05 Min. :0.02562
## 1st Qu.:1 1st Qu.:3.461e-05 1st Qu.:3.461e-05 1st Qu.:0.02562
## Median :1 Median :3.461e-05 Median :3.461e-05 Median :0.02562
## Mean :1 Mean :3.461e-05 Mean :3.461e-05 Mean :0.02562
## 3rd Qu.:1 3rd Qu.:3.461e-05 3rd Qu.:3.461e-05 3rd Qu.:0.02562
## Max. :1 Max. :3.461e-05 Max. :3.461e-05 Max. :0.02562MM.CPD <- glmer(abs.res.CPD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.CPD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.CPD.a <- anova(MM.CPD, test="Chisq")## Warning in anova.merMod(MM.CPD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001722 Min. :0.001722 Min. :2.627
## 1st Qu.:1 1st Qu.:0.001722 1st Qu.:0.001722 1st Qu.:2.627
## Median :1 Median :0.001722 Median :0.001722 Median :2.627
## Mean :1 Mean :0.001722 Mean :0.001722 Mean :2.627
## 3rd Qu.:1 3rd Qu.:0.001722 3rd Qu.:0.001722 3rd Qu.:2.627
## Max. :1 Max. :0.001722 Max. :0.001722 Max. :2.627MM.CPL <- glmer(abs.res.CPL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.CPL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.CPL.a <- anova(MM.CPL, test="Chisq")## Warning in anova.merMod(MM.CPL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0004791 Min. :0.0004791 Min. :0.5381
## 1st Qu.:1 1st Qu.:0.0004791 1st Qu.:0.0004791 1st Qu.:0.5381
## Median :1 Median :0.0004791 Median :0.0004791 Median :0.5381
## Mean :1 Mean :0.0004791 Mean :0.0004791 Mean :0.5381
## 3rd Qu.:1 3rd Qu.:0.0004791 3rd Qu.:0.0004791 3rd Qu.:0.5381
## Max. :1 Max. :0.0004791 Max. :0.0004791 Max. :0.5381MM.PreDL <- glmer(abs.res.PreDL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.PreDL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.PreDL.a <- anova(MM.PreDL, test="Chisq")## Warning in anova.merMod(MM.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :2.76e-05 Min. :2.76e-05 Min. :0.06634
## 1st Qu.:1 1st Qu.:2.76e-05 1st Qu.:2.76e-05 1st Qu.:0.06634
## Median :1 Median :2.76e-05 Median :2.76e-05 Median :0.06634
## Mean :1 Mean :2.76e-05 Mean :2.76e-05 Mean :0.06634
## 3rd Qu.:1 3rd Qu.:2.76e-05 3rd Qu.:2.76e-05 3rd Qu.:0.06634
## Max. :1 Max. :2.76e-05 Max. :2.76e-05 Max. :0.06634MM.DbL <- glmer(abs.res.DbL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.DbL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.DbL.a <- anova(MM.DbL, test="Chisq")## Warning in anova.merMod(MM.DbL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :4.269e-05 Min. :4.269e-05 Min. :0.02331
## 1st Qu.:1 1st Qu.:4.269e-05 1st Qu.:4.269e-05 1st Qu.:0.02331
## Median :1 Median :4.269e-05 Median :4.269e-05 Median :0.02331
## Mean :1 Mean :4.269e-05 Mean :4.269e-05 Mean :0.02331
## 3rd Qu.:1 3rd Qu.:4.269e-05 3rd Qu.:4.269e-05 3rd Qu.:0.02331
## Max. :1 Max. :4.269e-05 Max. :4.269e-05 Max. :0.02331MM.HL <- glmer(abs.res.HL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HL.a <- anova(MM.HL, test="Chisq")## Warning in anova.merMod(MM.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001879 Min. :0.001879 Min. :1.941
## 1st Qu.:1 1st Qu.:0.001879 1st Qu.:0.001879 1st Qu.:1.941
## Median :1 Median :0.001879 Median :0.001879 Median :1.941
## Mean :1 Mean :0.001879 Mean :0.001879 Mean :1.941
## 3rd Qu.:1 3rd Qu.:0.001879 3rd Qu.:0.001879 3rd Qu.:1.941
## Max. :1 Max. :0.001879 Max. :0.001879 Max. :1.941MM.HD <- glmer(abs.res.HD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HD.a <- anova(MM.HD, test="Chisq")## Warning in anova.merMod(MM.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.701e-06 Min. :1.701e-06 Min. :0.001735
## 1st Qu.:1 1st Qu.:1.701e-06 1st Qu.:1.701e-06 1st Qu.:0.001735
## Median :1 Median :1.701e-06 Median :1.701e-06 Median :0.001735
## Mean :1 Mean :1.701e-06 Mean :1.701e-06 Mean :0.001735
## 3rd Qu.:1 3rd Qu.:1.701e-06 3rd Qu.:1.701e-06 3rd Qu.:0.001735
## Max. :1 Max. :1.701e-06 Max. :1.701e-06 Max. :0.001735MM.HW <- glmer(abs.res.HW ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HW ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HW.a <- anova(MM.HW, test="Chisq")## Warning in anova.merMod(MM.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.002504 Min. :0.002504 Min. :3.287
## 1st Qu.:1 1st Qu.:0.002504 1st Qu.:0.002504 1st Qu.:3.287
## Median :1 Median :0.002504 Median :0.002504 Median :3.287
## Mean :1 Mean :0.002504 Mean :0.002504 Mean :3.287
## 3rd Qu.:1 3rd Qu.:0.002504 3rd Qu.:0.002504 3rd Qu.:3.287
## Max. :1 Max. :0.002504 Max. :0.002504 Max. :3.287MM.SnL <- glmer(abs.res.SnL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.SnL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.SnL.a <- anova(MM.SnL, test="Chisq")## Warning in anova.merMod(MM.SnL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0005063 Min. :0.0005063 Min. :0.8551
## 1st Qu.:1 1st Qu.:0.0005063 1st Qu.:0.0005063 1st Qu.:0.8551
## Median :1 Median :0.0005063 Median :0.0005063 Median :0.8551
## Mean :1 Mean :0.0005063 Mean :0.0005063 Mean :0.8551
## 3rd Qu.:1 3rd Qu.:0.0005063 3rd Qu.:0.0005063 3rd Qu.:0.8551
## Max. :1 Max. :0.0005063 Max. :0.0005063 Max. :0.8551MM.OL <- glmer(abs.res.OL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.OL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.OL.a <- anova(MM.OL, test="Chisq")## Warning in anova.merMod(MM.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :4.43e-33 Min. :4.43e-33 Min. :1.904
## 1st Qu.:1 1st Qu.:4.43e-33 1st Qu.:4.43e-33 1st Qu.:1.904
## Median :1 Median :4.43e-33 Median :4.43e-33 Median :1.904
## Mean :1 Mean :4.43e-33 Mean :4.43e-33 Mean :1.904
## 3rd Qu.:1 3rd Qu.:4.43e-33 3rd Qu.:4.43e-33 3rd Qu.:1.904
## Max. :1 Max. :4.43e-33 Max. :4.43e-33 Max. :1.904Watershed nested in Basin
MM1.D <- glmer(abs.res.D ~ SPP + (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.D ~ SPP + (1 | BASIN/WATERSHED), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.D.a <- anova(MM1.D, test="Chisq")## Warning in anova.merMod(MM1.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.01821 Min. :0.01821 Min. :0.1157
## 1st Qu.:1 1st Qu.:0.01821 1st Qu.:0.01821 1st Qu.:0.1157
## Median :1 Median :0.01821 Median :0.01821 Median :0.1157
## Mean :1 Mean :0.01821 Mean :0.01821 Mean :0.1157
## 3rd Qu.:1 3rd Qu.:0.01821 3rd Qu.:0.01821 3rd Qu.:0.1157
## Max. :1 Max. :0.01821 Max. :0.01821 Max. :0.1157MM1.P1 <- glmer(abs.res.P1 ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.P1 ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.P1.a <- anova(MM1.P1, test="Chisq")## Warning in anova.merMod(MM1.P1, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.P1.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.2476 Min. :0.2476 Min. :1.363
## 1st Qu.:1 1st Qu.:0.2476 1st Qu.:0.2476 1st Qu.:1.363
## Median :1 Median :0.2476 Median :0.2476 Median :1.363
## Mean :1 Mean :0.2476 Mean :0.2476 Mean :1.363
## 3rd Qu.:1 3rd Qu.:0.2476 3rd Qu.:0.2476 3rd Qu.:1.363
## Max. :1 Max. :0.2476 Max. :0.2476 Max. :1.363MM1.P1.R <- glmer(abs.res.P1.R ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.P1.R ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.P1.Ra <- anova(MM1.P1.R, test="Chisq")## Warning in anova.merMod(MM1.P1.R, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.798 Min. :1.798 Min. :11.61
## 1st Qu.:1 1st Qu.:1.798 1st Qu.:1.798 1st Qu.:11.61
## Median :1 Median :1.798 Median :1.798 Median :11.61
## Mean :1 Mean :1.798 Mean :1.798 Mean :11.61
## 3rd Qu.:1 3rd Qu.:1.798 3rd Qu.:1.798 3rd Qu.:11.61
## Max. :1 Max. :1.798 Max. :1.798 Max. :11.61MM1.LLSC <- glmer(abs.res.LLSC ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.LLSC ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.LLSC.a <- anova(MM1.LLSC, test="Chisq")## Warning in anova.merMod(MM1.LLSC, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.8627 Min. :0.8627 Min. :2
## 1st Qu.:1 1st Qu.:0.8627 1st Qu.:0.8627 1st Qu.:2
## Median :1 Median :0.8627 Median :0.8627 Median :2
## Mean :1 Mean :0.8627 Mean :0.8627 Mean :2
## 3rd Qu.:1 3rd Qu.:0.8627 3rd Qu.:0.8627 3rd Qu.:2
## Max. :1 Max. :0.8627 Max. :0.8627 Max. :2MM1.SBLL <- glmer(abs.res.SBLL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.SBLL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.SBLL.a <- anova(MM1.SBLL, test="Chisq")## Warning in anova.merMod(MM1.SBLL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.3889 Min. :0.3889 Min. :2.989
## 1st Qu.:1 1st Qu.:0.3889 1st Qu.:0.3889 1st Qu.:2.989
## Median :1 Median :0.3889 Median :0.3889 Median :2.989
## Mean :1 Mean :0.3889 Mean :0.3889 Mean :2.989
## 3rd Qu.:1 3rd Qu.:0.3889 3rd Qu.:0.3889 3rd Qu.:2.989
## Max. :1 Max. :0.3889 Max. :0.3889 Max. :2.989MM1.BD <- glmer(abs.res.BD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.BD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.BD.a <- anova(MM1.BD, test="Chisq")## Warning in anova.merMod(MM1.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0009062 Min. :0.0009062 Min. :0.7214
## 1st Qu.:1 1st Qu.:0.0009062 1st Qu.:0.0009062 1st Qu.:0.7214
## Median :1 Median :0.0009062 Median :0.0009062 Median :0.7214
## Mean :1 Mean :0.0009062 Mean :0.0009062 Mean :0.7214
## 3rd Qu.:1 3rd Qu.:0.0009062 3rd Qu.:0.0009062 3rd Qu.:0.7214
## Max. :1 Max. :0.0009062 Max. :0.0009062 Max. :0.7214MM1.CPD <- glmer(abs.res.CPD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.CPD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.CPD.a <- anova(MM1.CPD, test="Chisq")## Warning in anova.merMod(MM1.CPD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001731 Min. :0.001731 Min. :2.71
## 1st Qu.:1 1st Qu.:0.001731 1st Qu.:0.001731 1st Qu.:2.71
## Median :1 Median :0.001731 Median :0.001731 Median :2.71
## Mean :1 Mean :0.001731 Mean :0.001731 Mean :2.71
## 3rd Qu.:1 3rd Qu.:0.001731 3rd Qu.:0.001731 3rd Qu.:2.71
## Max. :1 Max. :0.001731 Max. :0.001731 Max. :2.71MM1.CPL <- glmer(abs.res.CPL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.CPL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.CPL.a <- anova(MM1.CPL, test="Chisq")## Warning in anova.merMod(MM1.CPL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0002359 Min. :0.0002359 Min. :0.2876
## 1st Qu.:1 1st Qu.:0.0002359 1st Qu.:0.0002359 1st Qu.:0.2876
## Median :1 Median :0.0002359 Median :0.0002359 Median :0.2876
## Mean :1 Mean :0.0002359 Mean :0.0002359 Mean :0.2876
## 3rd Qu.:1 3rd Qu.:0.0002359 3rd Qu.:0.0002359 3rd Qu.:0.2876
## Max. :1 Max. :0.0002359 Max. :0.0002359 Max. :0.2876MM1.PreDL <- glmer(abs.res.PreDL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.PreDL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.PreDL.a <- anova(MM1.PreDL, test="Chisq")## Warning in anova.merMod(MM1.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0004071 Min. :0.0004071 Min. :1.007
## 1st Qu.:1 1st Qu.:0.0004071 1st Qu.:0.0004071 1st Qu.:1.007
## Median :1 Median :0.0004071 Median :0.0004071 Median :1.007
## Mean :1 Mean :0.0004071 Mean :0.0004071 Mean :1.007
## 3rd Qu.:1 3rd Qu.:0.0004071 3rd Qu.:0.0004071 3rd Qu.:1.007
## Max. :1 Max. :0.0004071 Max. :0.0004071 Max. :1.007MM1.DbL <- glmer(abs.res.DbL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.DbL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.DbL.a <- anova(MM1.DbL, test="Chisq")## Warning in anova.merMod(MM1.DbL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0003223 Min. :0.0003223 Min. :0.1812
## 1st Qu.:1 1st Qu.:0.0003223 1st Qu.:0.0003223 1st Qu.:0.1812
## Median :1 Median :0.0003223 Median :0.0003223 Median :0.1812
## Mean :1 Mean :0.0003223 Mean :0.0003223 Mean :0.1812
## 3rd Qu.:1 3rd Qu.:0.0003223 3rd Qu.:0.0003223 3rd Qu.:0.1812
## Max. :1 Max. :0.0003223 Max. :0.0003223 Max. :0.1812MM1.HL <- glmer(abs.res.HL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.HL.a <- anova(MM1.HL, test="Chisq")## Warning in anova.merMod(MM1.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.697e-05 Min. :3.697e-05 Min. :0.04111
## 1st Qu.:1 1st Qu.:3.697e-05 1st Qu.:3.697e-05 1st Qu.:0.04111
## Median :1 Median :3.697e-05 Median :3.697e-05 Median :0.04111
## Mean :1 Mean :3.697e-05 Mean :3.697e-05 Mean :0.04111
## 3rd Qu.:1 3rd Qu.:3.697e-05 3rd Qu.:3.697e-05 3rd Qu.:0.04111
## Max. :1 Max. :3.697e-05 Max. :3.697e-05 Max. :0.04111MM1.HD <- glmer(abs.res.HD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.HD.a <- anova(MM1.HD, test="Chisq")## Warning in anova.merMod(MM1.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :9.321e-06 Min. :9.321e-06 Min. :0.009664
## 1st Qu.:1 1st Qu.:9.321e-06 1st Qu.:9.321e-06 1st Qu.:0.009664
## Median :1 Median :9.321e-06 Median :9.321e-06 Median :0.009664
## Mean :1 Mean :9.321e-06 Mean :9.321e-06 Mean :0.009664
## 3rd Qu.:1 3rd Qu.:9.321e-06 3rd Qu.:9.321e-06 3rd Qu.:0.009664
## Max. :1 Max. :9.321e-06 Max. :9.321e-06 Max. :0.009664MM1.HW <- glmer(abs.res.HW ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HW ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.HW.a <- anova(MM1.HW, test="Chisq")## Warning in anova.merMod(MM1.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.004251 Min. :0.004251 Min. :5.681
## 1st Qu.:1 1st Qu.:0.004251 1st Qu.:0.004251 1st Qu.:5.681
## Median :1 Median :0.004251 Median :0.004251 Median :5.681
## Mean :1 Mean :0.004251 Mean :0.004251 Mean :5.681
## 3rd Qu.:1 3rd Qu.:0.004251 3rd Qu.:0.004251 3rd Qu.:5.681
## Max. :1 Max. :0.004251 Max. :0.004251 Max. :5.681MM1.SnL <- glmer(abs.res.SnL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.SnL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.SnL.a <- anova(MM1.SnL, test="Chisq")## Warning in anova.merMod(MM1.SnL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0003137 Min. :0.0003137 Min. :0.5899
## 1st Qu.:1 1st Qu.:0.0003137 1st Qu.:0.0003137 1st Qu.:0.5899
## Median :1 Median :0.0003137 Median :0.0003137 Median :0.5899
## Mean :1 Mean :0.0003137 Mean :0.0003137 Mean :0.5899
## 3rd Qu.:1 3rd Qu.:0.0003137 3rd Qu.:0.0003137 3rd Qu.:0.5899
## Max. :1 Max. :0.0003137 Max. :0.0003137 Max. :0.5899MM1.OL <- glmer(abs.res.OL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.OL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.OL.a <- anova(MM1.OL, test="Chisq")## Warning in anova.merMod(MM1.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.795e-33 Min. :3.795e-33 Min. :1.62
## 1st Qu.:1 1st Qu.:3.795e-33 1st Qu.:3.795e-33 1st Qu.:1.62
## Median :1 Median :3.795e-33 Median :3.795e-33 Median :1.62
## Mean :1 Mean :3.795e-33 Mean :3.795e-33 Mean :1.62
## 3rd Qu.:1 3rd Qu.:3.795e-33 3rd Qu.:3.795e-33 3rd Qu.:1.62
## Max. :1 Max. :3.795e-33 Max. :3.795e-33 Max. :1.62Levene’s w/ Basin?
Not sure if this is correct, but might try Levene’s test with zone/basin/watershed as an additional independent factor? This is for the traits that did NOT vary with body length.
Zones
library(car)## Loading required package: carData##
## Attaching package: 'car'## The following object is masked from 'package:dplyr':
##
## recode(LT2_P2L <- leveneTest(P2.L~SPP*QUARTILE, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 292(LT2_P2R <- leveneTest(P2.R~SPP*QUARTILE, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 292(LT2_A <- leveneTest(A~SPP*QUARTILE, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.0512 0.3954
## 292(LT2_SALL <- leveneTest(SALL~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 10.093 2.613e-11 ***
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.1533 0.3299
## 292(LT2_SBDF <- leveneTest(SBDF~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 2.0714 0.04655 *
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 3.5457 0.001129 **
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Basins
(LT2_P2L <- leveneTest(P2.L~SPP*BASIN, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 NaN NaN
## 289(LT2_P2R <- leveneTest(P2.R~SPP*BASIN, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 NaN NaN
## 289(LT2_A <- leveneTest(A~SPP*BASIN, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 2.7914 0.002593 **
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SALL <- leveneTest(SALL~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 10.224 9.633e-15 ***
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 1.467 0.1511
## 289(LT2_SBDF <- leveneTest(SBDF~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 3.3639 0.0003629 ***
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 1.4055 0.177
## 289Watersheds
(LT2_P2L <- leveneTest(P2.L~SPP*WATERSHED, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 NaN NaN
## 280(LT2_P2R <- leveneTest(P2.R~SPP*WATERSHED, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 NaN NaN
## 280(LT2_A <- leveneTest(A~SPP*WATERSHED, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 1.4755 0.09315 .
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SALL <- leveneTest(SALL~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 4.7794 1.266e-09 ***
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 2.0999 0.005256 **
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBDF <- leveneTest(SBDF~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 2.0915 0.005484 **
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 1.8711 0.01617 *
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Filtered data
Now I will repeat analysis on a dataset that filters for fish above 32.5mm (this is the average for the range I found in literature, 28-37mm). This would confirm that all fish are likely adults, and remove any bias from juvenile proportions (ex. if juvenile head is proportionately larger than expected for body).
Initial steps
Data collection
## [1] 0.5690529## [1] 0.5782063## [1] 0.7316606## [1] 0.274228## [1] 0.03134439## [1] 0.03008961## [1] 0.031172## [1] 0.04262162## [1] 0.04095673## [1] 0.02983505## [1] 0.02970775## [1] 0.02753679## [1] 0.02404323## [1] 4.47166e-18## [1] 0.5057929## [1] 0.4644069## [1] 0.8024266## [1] 0.3032569## [1] 0.03633792## [1] 0.02681247## [1] 0.03066026## [1] 0.04651937## [1] 0.03191869## [1] 0.03006365## [1] 0.02822344## [1] 0.02989707## [1] 0.02797642## [1] 2.211292e-17## [1] 0.09391999## [1] 0.5711081## [1] 0.4403132## [1] 0.2860922## [1] 0.03040541## [1] 0.02942755## [1] 0.0309752## [1] 0.04357568## [1] 0.02689813## [1] 0.04816588## [1] 0.0318384## [1] 0.02994677## [1] 0.03665857## [1] 3.901712e-18ANOVAs
Amazon
Zones
library(ggplot2)
Flat3 <- rawF2[rawF2$SPP == "p.latipinna", ]
Fform3 <- rawF2[rawF2$SPP == "p.latipinna", ]
FA.D.F <- aov(F.abs.res.D ~ QUARTILE, data=Fform3)
summary(FA.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.418 0.4726 2.458 0.0683 .
## Residuals 86 16.538 0.1923
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.D)) +
geom_boxplot()
FA.P1.R.F <- aov(F.abs.res.P1.R ~ QUARTILE, data=Fform3)
summary(FA.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.402 0.1341 0.852 0.469
## Residuals 86 13.538 0.1574ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.P1.R)) +
geom_boxplot()
FA.LLSC.F <- aov(F.abs.res.LLSC ~ QUARTILE, data=Fform3)
summary(FA.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.17 0.3897 0.927 0.431
## Residuals 86 36.16 0.4205FA.SBLL.F <- aov(F.abs.res.SBLL ~ QUARTILE, data=Fform3)
summary(FA.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.652 0.2173 1.584 0.199
## Residuals 86 11.796 0.1372ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.SBLL)) +
geom_boxplot()
FA.BD.F <- aov(F.abs.res.BD ~ QUARTILE, data=Fform3)
summary(FA.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00394 0.0013126 1.805 0.152
## Residuals 86 0.06254 0.0007272ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.BD)) +
geom_boxplot()
FA.CPD.F <- aov(F.abs.res.CPD ~ QUARTILE, data=Fform3)
summary(FA.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00758 0.0025254 5.477 0.00171 **
## Residuals 86 0.03965 0.0004611
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.CPD)) +
geom_boxplot()
FA.CPL.F <- aov(F.abs.res.CPL ~ QUARTILE, data=Fform3)
summary(FA.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00987 0.003290 4.95 0.00322 **
## Residuals 86 0.05715 0.000665
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.CPL)) +
geom_boxplot()
FA.PreDL.F <- aov(F.abs.res.PreDL ~ QUARTILE, data=Fform3)
summary(FA.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00673 0.002243 1.957 0.127
## Residuals 86 0.09857 0.001146ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.PreDL)) +
geom_boxplot()
FA.DbL.F <- aov(F.abs.res.DbL ~ QUARTILE, data=Fform3)
summary(FA.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01943 0.006478 11.04 3.33e-06 ***
## Residuals 86 0.05045 0.000587
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.DbL)) +
geom_boxplot()
FA.HL.F <- aov(F.abs.res.HL ~ QUARTILE, data=Fform3)
summary(FA.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00235 0.0007843 1.135 0.339
## Residuals 86 0.05941 0.0006908ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.HL)) +
geom_boxplot()
FA.HD.F <- aov(F.abs.res.HD ~ QUARTILE, data=Fform3)
summary(FA.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00052 0.0001745 0.302 0.824
## Residuals 86 0.04976 0.0005786FA.HW.F <- aov(F.abs.res.HW ~ QUARTILE, data=Fform3)
summary(FA.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00245 0.0008175 1.729 0.167
## Residuals 86 0.04066 0.0004728ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.HW)) +
geom_boxplot()
FA.SnL.F <- aov(F.abs.res.SnL ~ QUARTILE, data=Fform3)
summary(FA.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00430 0.0014333 3.525 0.0183 *
## Residuals 86 0.03497 0.0004066
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA.OL.F <- aov(F.abs.res.OL ~ QUARTILE, data=Fform3)
summary(FA.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 5.730e-34 1.909e-34 0.886 0.452
## Residuals 86 1.853e-32 2.154e-34ggplot(Fform3, aes(x=factor(QUARTILE), y=F.abs.res.OL)) +
geom_boxplot()
Basins
FA1.D.F <- aov(F.abs.res.D ~ BASIN, data=Fform3)
summary(FA1.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 1.928 0.6428 3.449 0.0201 *
## Residuals 86 16.027 0.1864
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.D)) +
geom_boxplot()
FA1.P1.R.F <- aov(F.abs.res.P1.R ~ BASIN, data=Fform3)
summary(FA1.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.374 0.1246 0.79 0.503
## Residuals 86 13.566 0.1578ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.P1.R)) +
geom_boxplot()
FA1.LLSC.F <- aov(F.abs.res.LLSC ~ BASIN, data=Fform3)
summary(FA1.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 4.14 1.3806 3.577 0.0172 *
## Residuals 86 33.19 0.3859
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.LLSC)) +
geom_boxplot()
FA1.SBLL.F <- aov(F.abs.res.SBLL ~ BASIN, data=Fform3)
summary(FA1.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.445 0.1483 1.062 0.369
## Residuals 86 12.003 0.1396ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.SBLL)) +
geom_boxplot()
FA1.BD.F <- aov(F.abs.res.BD ~ BASIN, data=Fform3)
summary(FA1.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00191 0.0006374 0.849 0.471
## Residuals 86 0.06456 0.0007507ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.BD)) +
geom_boxplot()
FA1.CPD.F <- aov(F.abs.res.CPD ~ BASIN, data=Fform3)
summary(FA1.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00774 0.0025790 5.616 0.00145 **
## Residuals 86 0.03949 0.0004592
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.CPD)) +
geom_boxplot()
FA1.CPL.F <- aov(F.abs.res.CPL ~ BASIN, data=Fform3)
summary(FA1.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00820 0.002734 3.998 0.0102 *
## Residuals 86 0.05882 0.000684
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA1.PreDL.F <- aov(F.abs.res.PreDL ~ BASIN, data=Fform3)
summary(FA1.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00735 0.002451 2.153 0.0995 .
## Residuals 86 0.09794 0.001139
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.PreDL)) +
geom_boxplot()
FA1.DbL.F <- aov(F.abs.res.DbL ~ BASIN, data=Fform3)
summary(FA1.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.01801 0.006003 9.952 1.06e-05 ***
## Residuals 86 0.05188 0.000603
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.DbL)) +
geom_boxplot()
FA1.HL.F <- aov(F.abs.res.HL ~ BASIN, data=Fform3)
summary(FA1.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00068 0.0002282 0.321 0.81
## Residuals 86 0.06108 0.0007102ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.HL)) +
geom_boxplot()
FA1.HD.F <- aov(F.abs.res.HD ~ BASIN, data=Fform3)
summary(FA1.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00122 0.0004079 0.715 0.546
## Residuals 86 0.04906 0.0005704ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.HD)) +
geom_boxplot()
FA1.HW.F <- aov(F.abs.res.HW ~ BASIN, data=Fform3)
summary(FA1.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00382 0.001272 2.785 0.0456 *
## Residuals 86 0.03930 0.000457
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.HW)) +
geom_boxplot()
FA1.SnL.F <- aov(F.abs.res.SnL ~ BASIN, data=Fform3)
summary(FA1.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00195 0.0006514 1.501 0.22
## Residuals 86 0.03732 0.0004339FA1.OL.F <- aov(F.abs.res.OL ~ BASIN, data=Fform3)
summary(FA1.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 4.180e-34 1.395e-34 0.642 0.59
## Residuals 86 1.868e-32 2.172e-34ggplot(Fform3, aes(x=factor(BASIN), y=F.abs.res.OL)) +
geom_boxplot()
Watersheds
FA2.D.F <- aov(F.abs.res.D ~ WATERSHED, data=Fform3)
summary(FA2.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 2.528 0.3611 1.919 0.0768 .
## Residuals 82 15.428 0.1881
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.D)) +
geom_boxplot()
FA2.P1.R.F <- aov(F.abs.res.P1.R ~ WATERSHED, data=Fform3)
summary(FA2.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.549 0.07841 0.48 0.846
## Residuals 82 13.391 0.16331ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.P1.R)) +
geom_boxplot()
FA2.LLSC.F <- aov(F.abs.res.LLSC ~ WATERSHED, data=Fform3)
summary(FA2.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 7.038 1.0054 2.721 0.0137 *
## Residuals 82 30.294 0.3694
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.LLSC)) +
geom_boxplot()
FA2.SBLL.F <- aov(F.abs.res.SBLL ~ WATERSHED, data=Fform3)
summary(FA2.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 5.967 0.8525 10.79 1.45e-09 ***
## Residuals 82 6.480 0.0790
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.SBLL)) +
geom_boxplot()
FA2.BD.F <- aov(F.abs.res.BD ~ WATERSHED, data=Fform3)
summary(FA2.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00987 0.0014097 2.042 0.0594 .
## Residuals 82 0.05661 0.0006903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.BD)) +
geom_boxplot()
FA2.CPD.F <- aov(F.abs.res.CPD ~ WATERSHED, data=Fform3)
summary(FA2.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00919 0.0013132 2.831 0.0108 *
## Residuals 82 0.03803 0.0004638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.CPD)) +
geom_boxplot()
FA2.CPL.F <- aov(F.abs.res.CPL ~ WATERSHED, data=Fform3)
summary(FA2.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01335 0.0019073 2.914 0.00899 **
## Residuals 82 0.05367 0.0006545
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.PreDL.F <- aov(F.abs.res.PreDL ~ WATERSHED, data=Fform3)
summary(FA2.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01354 0.001935 1.729 0.114
## Residuals 82 0.09175 0.001119FA2.DbL.F <- aov(F.abs.res.DbL ~ WATERSHED, data=Fform3)
summary(FA2.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01952 0.0027884 4.539 0.000255 ***
## Residuals 82 0.05037 0.0006143
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.DbL)) +
geom_boxplot()
FA2.HL.F <- aov(F.abs.res.HL ~ WATERSHED, data=Fform3)
summary(FA2.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00391 0.0005587 0.792 0.596
## Residuals 82 0.05785 0.0007055ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.HL)) +
geom_boxplot()
FA2.HD.F <- aov(F.abs.res.HD ~ WATERSHED, data=Fform3)
summary(FA2.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00195 0.0002780 0.472 0.852
## Residuals 82 0.04833 0.0005894ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.HD)) +
geom_boxplot()
FA2.HW.F <- aov(F.abs.res.HW ~ WATERSHED, data=Fform3)
summary(FA2.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00569 0.0008128 1.781 0.102
## Residuals 82 0.03743 0.0004564ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.HW)) +
geom_boxplot()
FA2.SnL.F <- aov(F.abs.res.SnL ~ WATERSHED, data=Fform3)
summary(FA2.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00601 0.0008592 2.118 0.0505 .
## Residuals 82 0.03326 0.0004056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.OL.F <- aov(F.abs.res.OL ~ WATERSHED, data=Fform3)
summary(FA2.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 8.180e-34 1.169e-34 0.524 0.814
## Residuals 82 1.828e-32 2.229e-34ggplot(Fform3, aes(x=factor(WATERSHED), y=F.abs.res.OL)) +
geom_boxplot()
Sailfin
Zones
library(ggplot2)
FA.D.L <- aov(F.abs.res.D ~ QUARTILE, data=Flat3)
summary(FA.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.418 0.4726 2.458 0.0683 .
## Residuals 86 16.538 0.1923
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.D)) +
geom_boxplot()
FA.P1.R.L <- aov(F.abs.res.P1.R ~ QUARTILE, data=Flat3)
summary(FA.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.402 0.1341 0.852 0.469
## Residuals 86 13.538 0.1574ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.P1.R)) +
geom_boxplot()
FA.LLSC.L <- aov(F.abs.res.LLSC ~ QUARTILE, data=Flat3)
summary(FA.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.17 0.3897 0.927 0.431
## Residuals 86 36.16 0.4205FA.SBLL.L <- aov(F.abs.res.SBLL ~ QUARTILE, data=Flat3)
summary(FA.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.652 0.2173 1.584 0.199
## Residuals 86 11.796 0.1372ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.SBLL)) +
geom_boxplot()
FA.BD.L <- aov(F.abs.res.BD ~ QUARTILE, data=Flat3)
summary(FA.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00394 0.0013126 1.805 0.152
## Residuals 86 0.06254 0.0007272ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.BD)) +
geom_boxplot()
FA.CPD.L <- aov(F.abs.res.CPD ~ QUARTILE, data=Flat3)
summary(FA.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00758 0.0025254 5.477 0.00171 **
## Residuals 86 0.03965 0.0004611
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.CPD)) +
geom_boxplot()
FA.CPL.L <- aov(F.abs.res.CPL ~ QUARTILE, data=Flat3)
summary(FA.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00987 0.003290 4.95 0.00322 **
## Residuals 86 0.05715 0.000665
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.CPL)) +
geom_boxplot()
FA.PreDL.L <- aov(F.abs.res.PreDL ~ QUARTILE, data=Flat3)
summary(FA.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00673 0.002243 1.957 0.127
## Residuals 86 0.09857 0.001146ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.PreDL)) +
geom_boxplot()
FA.DbL.L <- aov(F.abs.res.DbL ~ QUARTILE, data=Flat3)
summary(FA.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01943 0.006478 11.04 3.33e-06 ***
## Residuals 86 0.05045 0.000587
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.DbL)) +
geom_boxplot()
FA.HL.L <- aov(F.abs.res.HL ~ QUARTILE, data=Flat3)
summary(FA.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00235 0.0007843 1.135 0.339
## Residuals 86 0.05941 0.0006908ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.HL)) +
geom_boxplot()
FA.HD.L <- aov(F.abs.res.HD ~ QUARTILE, data=Flat3)
summary(FA.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00052 0.0001745 0.302 0.824
## Residuals 86 0.04976 0.0005786FA.HW.L <- aov(F.abs.res.HW ~ QUARTILE, data=Flat3)
summary(FA.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00245 0.0008175 1.729 0.167
## Residuals 86 0.04066 0.0004728ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.HW)) +
geom_boxplot()
FA.SnL.L <- aov(F.abs.res.SnL ~ QUARTILE, data=Flat3)
summary(FA.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00430 0.0014333 3.525 0.0183 *
## Residuals 86 0.03497 0.0004066
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA.OL.L <- aov(F.abs.res.OL ~ QUARTILE, data=Flat3)
summary(FA.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 5.730e-34 1.909e-34 0.886 0.452
## Residuals 86 1.853e-32 2.154e-34ggplot(Flat3, aes(x=factor(QUARTILE), y=F.abs.res.OL)) +
geom_boxplot()
Basins
FA1.D.L <- aov(F.abs.res.D ~ BASIN, data=Flat3)
summary(FA1.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 1.928 0.6428 3.449 0.0201 *
## Residuals 86 16.027 0.1864
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.D)) +
geom_boxplot()
FA1.P1.R.L <- aov(F.abs.res.P1.R ~ BASIN, data=Flat3)
summary(FA1.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.374 0.1246 0.79 0.503
## Residuals 86 13.566 0.1578ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.P1.R)) +
geom_boxplot()
FA1.LLSC.L <- aov(F.abs.res.LLSC ~ BASIN, data=Flat3)
summary(FA1.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 4.14 1.3806 3.577 0.0172 *
## Residuals 86 33.19 0.3859
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.LLSC)) +
geom_boxplot()
FA1.SBLL.L <- aov(F.abs.res.SBLL ~ BASIN, data=Flat3)
summary(FA1.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.445 0.1483 1.062 0.369
## Residuals 86 12.003 0.1396ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.SBLL)) +
geom_boxplot()
FA1.BD.L <- aov(F.abs.res.BD ~ BASIN, data=Flat3)
summary(FA1.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00191 0.0006374 0.849 0.471
## Residuals 86 0.06456 0.0007507ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.BD)) +
geom_boxplot()
FA1.CPD.L <- aov(F.abs.res.CPD ~ BASIN, data=Flat3)
summary(FA1.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00774 0.0025790 5.616 0.00145 **
## Residuals 86 0.03949 0.0004592
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.CPD)) +
geom_boxplot()
FA1.CPL.L <- aov(F.abs.res.CPL ~ BASIN, data=Flat3)
summary(FA1.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00820 0.002734 3.998 0.0102 *
## Residuals 86 0.05882 0.000684
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA1.PreDL.L <- aov(F.abs.res.PreDL ~ BASIN, data=Flat3)
summary(FA1.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00735 0.002451 2.153 0.0995 .
## Residuals 86 0.09794 0.001139
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.PreDL)) +
geom_boxplot()
FA1.DbL.L <- aov(F.abs.res.DbL ~ BASIN, data=Flat3)
summary(FA1.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.01801 0.006003 9.952 1.06e-05 ***
## Residuals 86 0.05188 0.000603
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.DbL)) +
geom_boxplot()
FA1.HL.L <- aov(F.abs.res.HL ~ BASIN, data=Flat3)
summary(FA1.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00068 0.0002282 0.321 0.81
## Residuals 86 0.06108 0.0007102ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.HL)) +
geom_boxplot()
FA1.HD.L <- aov(F.abs.res.HD ~ BASIN, data=Flat3)
summary(FA1.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00122 0.0004079 0.715 0.546
## Residuals 86 0.04906 0.0005704ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.HD)) +
geom_boxplot()
FA1.HW.L <- aov(F.abs.res.HW ~ BASIN, data=Flat3)
summary(FA1.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00382 0.001272 2.785 0.0456 *
## Residuals 86 0.03930 0.000457
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.HW)) +
geom_boxplot()
FA1.SnL.L <- aov(F.abs.res.SnL ~ BASIN, data=Flat3)
summary(FA1.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 0.00195 0.0006514 1.501 0.22
## Residuals 86 0.03732 0.0004339FA1.OL.L <- aov(F.abs.res.OL ~ BASIN, data=Flat3)
summary(FA1.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 3 4.180e-34 1.395e-34 0.642 0.59
## Residuals 86 1.868e-32 2.172e-34ggplot(Flat3, aes(x=factor(BASIN), y=F.abs.res.OL)) +
geom_boxplot()
Watersheds
FA2.D.L <- aov(F.abs.res.D ~ WATERSHED, data=Flat3)
summary(FA2.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 2.528 0.3611 1.919 0.0768 .
## Residuals 82 15.428 0.1881
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.D)) +
geom_boxplot()
ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.P1.R)) +
geom_boxplot()
FA2.LLSC.L <- aov(F.abs.res.LLSC ~ WATERSHED, data=Flat3)
summary(FA2.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 7.038 1.0054 2.721 0.0137 *
## Residuals 82 30.294 0.3694
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.LLSC)) +
geom_boxplot()
FA2.SBLL.L <- aov(F.abs.res.SBLL ~ WATERSHED, data=Flat3)
summary(FA2.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 5.967 0.8525 10.79 1.45e-09 ***
## Residuals 82 6.480 0.0790
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.SBLL)) +
geom_boxplot()
FA2.BD.L <- aov(F.abs.res.BD ~ WATERSHED, data=Flat3)
summary(FA2.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00987 0.0014097 2.042 0.0594 .
## Residuals 82 0.05661 0.0006903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.BD)) +
geom_boxplot()
FA2.CPD.L <- aov(F.abs.res.CPD ~ WATERSHED, data=Flat3)
summary(FA2.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00919 0.0013132 2.831 0.0108 *
## Residuals 82 0.03803 0.0004638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.CPD)) +
geom_boxplot()
FA2.CPL.L <- aov(F.abs.res.CPL ~ WATERSHED, data=Flat3)
summary(FA2.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01335 0.0019073 2.914 0.00899 **
## Residuals 82 0.05367 0.0006545
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.PreDL.L <- aov(F.abs.res.PreDL ~ WATERSHED, data=Flat3)
summary(FA2.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01354 0.001935 1.729 0.114
## Residuals 82 0.09175 0.001119FA2.DbL.L <- aov(F.abs.res.DbL ~ WATERSHED, data=Flat3)
summary(FA2.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.01952 0.0027884 4.539 0.000255 ***
## Residuals 82 0.05037 0.0006143
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.DbL)) +
geom_boxplot()
FA2.HL.L <- aov(F.abs.res.HL ~ WATERSHED, data=Flat3)
summary(FA2.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00391 0.0005587 0.792 0.596
## Residuals 82 0.05785 0.0007055ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.HL)) +
geom_boxplot()
FA2.HD.L <- aov(F.abs.res.HD ~ WATERSHED, data=Flat3)
summary(FA2.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00195 0.0002780 0.472 0.852
## Residuals 82 0.04833 0.0005894ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.HD)) +
geom_boxplot()
FA2.HW.L <- aov(F.abs.res.HW ~ WATERSHED, data=Flat3)
summary(FA2.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00569 0.0008128 1.781 0.102
## Residuals 82 0.03743 0.0004564ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.HW)) +
geom_boxplot()
FA2.SnL.L <- aov(F.abs.res.SnL ~ WATERSHED, data=Flat3)
summary(FA2.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 0.00601 0.0008592 2.118 0.0505 .
## Residuals 82 0.03326 0.0004056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.OL.L <- aov(F.abs.res.OL ~ WATERSHED, data=Flat3)
summary(FA2.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 8.180e-34 1.169e-34 0.524 0.814
## Residuals 82 1.828e-32 2.229e-34ggplot(Flat3, aes(x=factor(WATERSHED), y=F.abs.res.OL)) +
geom_boxplot()
Both
Zones
library(ggplot2)
FA.D <- aov(F.abs.res.D ~ SPP*QUARTILE, data=Fraw3)
summary(FA.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.196 0.1956 1.295 0.257
## QUARTILE 3 0.613 0.2042 1.352 0.259
## SPP:QUARTILE 3 0.823 0.2742 1.816 0.146
## Residuals 189 28.545 0.1510ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.D, fill=SPP)) +
geom_boxplot()
FA.P1.R <- aov(F.abs.res.P1.R ~ SPP*QUARTILE, data=Fraw3)
summary(FA.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.63 0.6331 3.660 0.0573 .
## QUARTILE 3 0.44 0.1475 0.853 0.4667
## SPP:QUARTILE 3 0.11 0.0360 0.208 0.8907
## Residuals 189 32.69 0.1730
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.P1.R, fill=SPP)) +
geom_boxplot()
FA.LLSC <- aov(F.abs.res.LLSC ~ SPP*QUARTILE, data=Fraw3)
summary(FA.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.24 0.2448 0.556 0.457
## QUARTILE 3 1.02 0.3385 0.768 0.513
## SPP:QUARTILE 3 2.05 0.6829 1.551 0.203
## Residuals 189 83.24 0.4404FA.SBLL <- aov(F.abs.res.SBLL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.041 0.0412 0.300 0.5846
## QUARTILE 3 0.958 0.3192 2.325 0.0763 .
## SPP:QUARTILE 3 0.632 0.2108 1.535 0.2069
## Residuals 189 25.955 0.1373
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.SBLL, fill=SPP)) +
geom_boxplot()
FA.BD <- aov(F.abs.res.BD ~ SPP*QUARTILE, data=Fraw3)
summary(FA.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00122 0.0012189 1.475 0.226
## QUARTILE 3 0.00516 0.0017198 2.081 0.104
## SPP:QUARTILE 3 0.00134 0.0004464 0.540 0.655
## Residuals 189 0.15620 0.0008265ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.BD, fill=SPP)) +
geom_boxplot()
FA.CPD <- aov(F.abs.res.CPD ~ SPP*QUARTILE, data=Fraw3)
summary(FA.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00052 0.0005250 1.104 0.2947
## QUARTILE 3 0.00401 0.0013377 2.813 0.0406 *
## SPP:QUARTILE 3 0.00434 0.0014450 3.039 0.0303 *
## Residuals 189 0.08986 0.0004755
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.CPD, fill=SPP)) +
geom_boxplot()
FA.CPL <- aov(F.abs.res.CPL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00001 0.000013 0.018 0.89290
## QUARTILE 3 0.01017 0.003390 4.813 0.00297 **
## SPP:QUARTILE 3 0.00374 0.001248 1.772 0.15404
## Residuals 189 0.13311 0.000704
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.CPL, fill=SPP)) +
geom_boxplot()
FA.PreDL <- aov(F.abs.res.PreDL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00074 0.000743 0.586 0.4450
## QUARTILE 3 0.00147 0.000489 0.386 0.7633
## SPP:QUARTILE 3 0.01126 0.003753 2.960 0.0336 *
## Residuals 189 0.23962 0.001268
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.PreDL, fill=SPP)) +
geom_boxplot()
FA.DbL <- aov(F.abs.res.DbL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00399 0.003993 5.248 0.02308 *
## QUARTILE 3 0.01021 0.003402 4.471 0.00465 **
## SPP:QUARTILE 3 0.01222 0.004073 5.353 0.00147 **
## Residuals 189 0.14381 0.000761
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.DbL, fill=SPP)) +
geom_boxplot()
FA.HL <- aov(F.abs.res.HL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000026 0.004 0.9496
## QUARTILE 3 0.00530 0.0017669 2.772 0.0428 *
## SPP:QUARTILE 3 0.00187 0.0006220 0.976 0.4053
## Residuals 189 0.12047 0.0006374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.HL, fill=SPP)) +
geom_boxplot()
FA.HD <- aov(F.abs.res.HD ~ SPP*QUARTILE, data=Fraw3)
summary(FA.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00011 0.0001077 0.187 0.666
## QUARTILE 3 0.00142 0.0004720 0.818 0.486
## SPP:QUARTILE 3 0.00072 0.0002393 0.414 0.743
## Residuals 189 0.10911 0.0005773FA.HW <- aov(F.abs.res.HW ~ SPP*QUARTILE, data=Fraw3)
summary(FA.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00027 0.0002723 0.521 0.4714
## QUARTILE 3 0.00102 0.0003407 0.652 0.5828
## SPP:QUARTILE 3 0.00332 0.0011051 2.114 0.0999 .
## Residuals 189 0.09882 0.0005229
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.HW, fill=SPP)) +
geom_boxplot()
FA.SnL <- aov(F.abs.res.SnL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00076 0.0007562 1.754 0.1869
## QUARTILE 3 0.00648 0.0021585 5.008 0.0023 **
## SPP:QUARTILE 3 0.00141 0.0004701 1.091 0.3543
## Residuals 189 0.08146 0.0004310
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA.OL <- aov(F.abs.res.OL ~ SPP*QUARTILE, data=Fraw3)
summary(FA.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.520e-32 1.521e-32 2.241 0.136
## QUARTILE 3 2.590e-32 8.637e-33 1.272 0.285
## SPP:QUARTILE 3 1.310e-32 4.368e-33 0.643 0.588
## Residuals 189 1.283e-30 6.789e-33ggplot(Fraw3, aes(x=factor(QUARTILE), y=F.abs.res.OL, fill=SPP)) +
geom_boxplot()
Basins
FA1.D <- aov(F.abs.res.D ~ SPP*BASIN, data=Fraw3)
summary(FA1.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.196 0.1956 1.318 0.2524
## BASIN 4 0.936 0.2340 1.576 0.1823
## SPP:BASIN 3 1.138 0.3792 2.555 0.0567 .
## Residuals 188 27.907 0.1484
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.D, fill=SPP)) +
geom_boxplot()
FA1.P1.R <- aov(F.abs.res.P1.R ~ SPP*BASIN, data=Fraw3)
summary(FA1.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.63 0.6331 3.630 0.0583 .
## BASIN 4 0.26 0.0651 0.373 0.8276
## SPP:BASIN 3 0.20 0.0668 0.383 0.7653
## Residuals 188 32.78 0.1744
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.P1.R, fill=SPP)) +
geom_boxplot()
FA1.LLSC <- aov(F.abs.res.LLSC ~ SPP*BASIN, data=Fraw3)
summary(FA1.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.24 0.2448 0.575 0.4494
## BASIN 4 4.07 1.0184 2.390 0.0524 .
## SPP:BASIN 3 2.14 0.7121 1.671 0.1746
## Residuals 188 80.10 0.4260
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.LLSC, fill=SPP)) +
geom_boxplot()
FA1.SBLL <- aov(F.abs.res.SBLL ~ SPP*BASIN, data=Fraw3)
summary(FA1.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.041 0.04119 0.296 0.587
## BASIN 4 0.813 0.20326 1.461 0.216
## SPP:BASIN 3 0.569 0.18980 1.364 0.255
## Residuals 188 26.163 0.13916ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.SBLL, fill=SPP)) +
geom_boxplot()
FA1.BD <- aov(F.abs.res.BD ~ SPP*BASIN, data=Fraw3)
summary(FA1.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00122 0.0012189 1.475 0.226
## BASIN 4 0.00612 0.0015295 1.851 0.121
## SPP:BASIN 3 0.00125 0.0004151 0.502 0.681
## Residuals 188 0.15534 0.0008263ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.BD, fill=SPP)) +
geom_boxplot()
FA1.CPD <- aov(F.abs.res.CPD ~ SPP*BASIN, data=Fraw3)
summary(FA1.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00052 0.0005250 1.102 0.2952
## BASIN 4 0.00335 0.0008368 1.756 0.1394
## SPP:BASIN 3 0.00530 0.0017682 3.712 0.0126 *
## Residuals 188 0.08956 0.0004764
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.CPD, fill=SPP)) +
geom_boxplot()
FA1.CPL <- aov(F.abs.res.CPL ~ SPP*BASIN, data=Fraw3)
summary(FA1.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00001 0.0000128 0.018 0.89317
## BASIN 4 0.01220 0.0030508 4.310 0.00233 **
## SPP:BASIN 3 0.00174 0.0005798 0.819 0.48484
## Residuals 188 0.13308 0.0007079
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA1.PreDL <- aov(F.abs.res.PreDL ~ SPP*BASIN, data=Fraw3)
summary(FA1.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00074 0.000743 0.591 0.4430
## BASIN 4 0.00628 0.001569 1.249 0.2918
## SPP:BASIN 3 0.00986 0.003287 2.616 0.0524 .
## Residuals 188 0.23621 0.001256
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.PreDL, fill=SPP)) +
geom_boxplot()
FA1.DbL <- aov(F.abs.res.DbL ~ SPP*BASIN, data=Fraw3)
summary(FA1.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00399 0.003993 5.074 0.02545 *
## BASIN 4 0.00653 0.001632 2.074 0.08586 .
## SPP:BASIN 3 0.01175 0.003916 4.975 0.00241 **
## Residuals 188 0.14796 0.000787
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.DbL, fill=SPP)) +
geom_boxplot()
FA1.HL <- aov(F.abs.res.HL ~ SPP*BASIN, data=Fraw3)
summary(FA1.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000026 0.004 0.951
## BASIN 4 0.00108 0.0002698 0.408 0.803
## SPP:BASIN 3 0.00213 0.0007092 1.072 0.362
## Residuals 188 0.12443 0.0006619ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.HL, fill=SPP)) +
geom_boxplot()
FA1.HD <- aov(F.abs.res.HD ~ SPP*BASIN, data=Fraw3)
summary(FA1.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00011 0.0001077 0.186 0.667
## BASIN 4 0.00221 0.0005533 0.957 0.433
## SPP:BASIN 3 0.00029 0.0000960 0.166 0.919
## Residuals 188 0.10875 0.0005784ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.HD, fill=SPP)) +
geom_boxplot()
FA1.HW <- aov(F.abs.res.HW ~ SPP*BASIN, data=Fraw3)
summary(FA1.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00027 0.0002723 0.521 0.471
## BASIN 4 0.00160 0.0004008 0.767 0.548
## SPP:BASIN 3 0.00329 0.0010963 2.097 0.102
## Residuals 188 0.09827 0.0005227ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.HW, fill=SPP)) +
geom_boxplot()
FA1.SnL <- aov(F.abs.res.SnL ~ SPP*BASIN, data=Fraw3)
summary(FA1.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00076 0.0007562 1.647 0.201
## BASIN 4 0.00240 0.0005994 1.305 0.270
## SPP:BASIN 3 0.00063 0.0002093 0.456 0.714
## Residuals 188 0.08632 0.0004592FA1.OL <- aov(F.abs.res.OL ~ SPP*BASIN, data=Fraw3)
summary(FA1.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.520e-32 1.521e-32 2.194 0.140
## BASIN 4 1.280e-32 3.194e-33 0.461 0.765
## SPP:BASIN 3 5.900e-33 1.953e-33 0.282 0.839
## Residuals 188 1.304e-30 6.934e-33ggplot(Fraw3, aes(x=factor(BASIN), y=F.abs.res.OL, fill=SPP)) +
geom_boxplot()
Watersheds
FA2.D <- aov(F.abs.res.D ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.196 0.1956 1.307 0.2545
## WATERSHED 9 1.293 0.1437 0.960 0.4749
## SPP:WATERSHED 5 1.594 0.3188 2.130 0.0639 .
## Residuals 181 27.093 0.1497
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.D, fill=SPP)) +
geom_boxplot()
FA2.P1.R <- aov(F.abs.res.P1.R ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.63 0.6331 3.529 0.0619 .
## WATERSHED 9 0.62 0.0691 0.385 0.9411
## SPP:WATERSHED 5 0.16 0.0315 0.176 0.9713
## Residuals 181 32.46 0.1794
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.P1.R, fill=SPP)) +
geom_boxplot()
FA2.LLSC <- aov(F.abs.res.LLSC ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.24 0.2448 0.622 0.43146
## WATERSHED 9 10.29 1.1428 2.902 0.00313 **
## SPP:WATERSHED 5 4.75 0.9493 2.411 0.03815 *
## Residuals 181 71.27 0.3938
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.LLSC, fill=SPP)) +
geom_boxplot()
FA2.SBLL <- aov(F.abs.res.SBLL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.041 0.0412 0.382 0.537499
## WATERSHED 9 3.471 0.3857 3.573 0.000411 ***
## SPP:WATERSHED 5 4.538 0.9076 8.409 3.58e-07 ***
## Residuals 181 19.536 0.1079
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.SBLL, fill=SPP)) +
geom_boxplot()
FA2.BD <- aov(F.abs.res.BD ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00122 0.0012189 1.554 0.214
## WATERSHED 9 0.00850 0.0009442 1.204 0.295
## SPP:WATERSHED 5 0.01223 0.0024455 3.118 0.010 *
## Residuals 181 0.14198 0.0007844
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.BD, fill=SPP)) +
geom_boxplot()
FA2.CPD <- aov(F.abs.res.CPD ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00052 0.0005250 1.085 0.2990
## WATERSHED 9 0.00504 0.0005601 1.157 0.3251
## SPP:WATERSHED 5 0.00558 0.0011161 2.306 0.0463 *
## Residuals 181 0.08759 0.0004839
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.CPD, fill=SPP)) +
geom_boxplot()
FA2.CPL <- aov(F.abs.res.CPL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00001 0.0000128 0.018 0.89268
## WATERSHED 9 0.01835 0.0020386 2.907 0.00308 **
## SPP:WATERSHED 5 0.00174 0.0003485 0.497 0.77826
## Residuals 181 0.12693 0.0007013
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.PreDL <- aov(F.abs.res.PreDL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00074 0.0007427 0.598 0.4403
## WATERSHED 9 0.02101 0.0023349 1.880 0.0574 .
## SPP:WATERSHED 5 0.00659 0.0013180 1.061 0.3834
## Residuals 181 0.22474 0.0012417
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.DbL <- aov(F.abs.res.DbL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00399 0.003993 5.100 0.02513 *
## WATERSHED 9 0.01205 0.001338 1.709 0.08966 .
## SPP:WATERSHED 5 0.01246 0.002493 3.184 0.00885 **
## Residuals 181 0.14173 0.000783
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.DbL, fill=SPP)) +
geom_boxplot()
FA2.HL <- aov(F.abs.res.HL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000026 0.004 0.9492
## WATERSHED 9 0.01195 0.0013275 2.118 0.0301 *
## SPP:WATERSHED 5 0.00222 0.0004441 0.708 0.6178
## Residuals 181 0.11347 0.0006269
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.HL, fill=SPP)) +
geom_boxplot()
FA2.HD <- aov(F.abs.res.HD ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00011 0.0001077 0.193 0.6608
## WATERSHED 9 0.00999 0.0011100 1.992 0.0426 *
## SPP:WATERSHED 5 0.00037 0.0000744 0.133 0.9845
## Residuals 181 0.10088 0.0005574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.HD, fill=SPP)) +
geom_boxplot()
FA2.HW <- aov(F.abs.res.HW ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00027 0.0002723 0.520 0.472
## WATERSHED 9 0.00419 0.0004657 0.889 0.536
## SPP:WATERSHED 5 0.00414 0.0008288 1.582 0.167
## Residuals 181 0.09482 0.0005239ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.HW, fill=SPP)) +
geom_boxplot()
FA2.SnL <- aov(F.abs.res.SnL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00076 0.0007562 1.758 0.1865
## WATERSHED 9 0.00944 0.0010493 2.440 0.0121 *
## SPP:WATERSHED 5 0.00207 0.0004133 0.961 0.4431
## Residuals 181 0.07784 0.0004300
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1FA2.OL <- aov(F.abs.res.OL ~ SPP*WATERSHED, data=Fraw3)
summary(FA2.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.520e-32 1.521e-32 2.167 0.143
## WATERSHED 9 4.530e-32 5.030e-33 0.717 0.693
## SPP:WATERSHED 5 6.400e-33 1.273e-33 0.181 0.969
## Residuals 181 1.271e-30 7.020e-33ggplot(Fraw3, aes(x=factor(WATERSHED), y=F.abs.res.OL, fill=SPP)) +
geom_boxplot()
GLMMs
Will run mixed models with zones/basins/watersheds as random effect. This will account for any variation seen at these levels and show us if there are any consistent species differences. Can only do this with residuals.
Zones
library(lme4)
library(lmerTest)
FMM.D <- glmer(F.abs.res.D ~ SPP + (1|QUARTILE), data=Fraw3)#originally had family=poisson, since this is count data, but because this was the residuals of count data, the values were non-integers and poisson only deals with integers. ## Warning in glmer(F.abs.res.D ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.D.a <- anova(FMM.D, test="Chisq")## Warning in anova.merMod(FMM.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.1854 Min. :0.1854 Min. :1.214
## 1st Qu.:1 1st Qu.:0.1854 1st Qu.:0.1854 1st Qu.:1.214
## Median :1 Median :0.1854 Median :0.1854 Median :1.214
## Mean :1 Mean :0.1854 Mean :0.1854 Mean :1.214
## 3rd Qu.:1 3rd Qu.:0.1854 3rd Qu.:0.1854 3rd Qu.:1.214
## Max. :1 Max. :0.1854 Max. :0.1854 Max. :1.214FMM.P1.R <- glmer(F.abs.res.P1.R ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.P1.R ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM.P1.Ra <- anova(FMM.P1.R, test="Chisq")## Warning in anova.merMod(FMM.P1.R, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.6331 Min. :0.6331 Min. :3.713
## 1st Qu.:1 1st Qu.:0.6331 1st Qu.:0.6331 1st Qu.:3.713
## Median :1 Median :0.6331 Median :0.6331 Median :3.713
## Mean :1 Mean :0.6331 Mean :0.6331 Mean :3.713
## 3rd Qu.:1 3rd Qu.:0.6331 3rd Qu.:0.6331 3rd Qu.:3.713
## Max. :1 Max. :0.6331 Max. :0.6331 Max. :3.713FMM.LLSC <- glmer(F.abs.res.LLSC ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.LLSC ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM.LLSC.a <- anova(FMM.LLSC, test="Chisq")## Warning in anova.merMod(FMM.LLSC, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.2448 Min. :0.2448 Min. :0.5531
## 1st Qu.:1 1st Qu.:0.2448 1st Qu.:0.2448 1st Qu.:0.5531
## Median :1 Median :0.2448 Median :0.2448 Median :0.5531
## Mean :1 Mean :0.2448 Mean :0.2448 Mean :0.5531
## 3rd Qu.:1 3rd Qu.:0.2448 3rd Qu.:0.2448 3rd Qu.:0.5531
## Max. :1 Max. :0.2448 Max. :0.2448 Max. :0.5531FMM.SBLL <- glmer(F.abs.res.SBLL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.SBLL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.SBLL.a <- anova(FMM.SBLL, test="Chisq")## Warning in anova.merMod(FMM.SBLL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0388 Min. :0.0388 Min. :0.2809
## 1st Qu.:1 1st Qu.:0.0388 1st Qu.:0.0388 1st Qu.:0.2809
## Median :1 Median :0.0388 Median :0.0388 Median :0.2809
## Mean :1 Mean :0.0388 Mean :0.0388 Mean :0.2809
## 3rd Qu.:1 3rd Qu.:0.0388 3rd Qu.:0.0388 3rd Qu.:0.2809
## Max. :1 Max. :0.0388 Max. :0.0388 Max. :0.2809FMM.BD <- glmer(F.abs.res.BD ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.BD ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.BD.a <- anova(FMM.BD, test="Chisq")## Warning in anova.merMod(FMM.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001192 Min. :0.001192 Min. :1.444
## 1st Qu.:1 1st Qu.:0.001192 1st Qu.:0.001192 1st Qu.:1.444
## Median :1 Median :0.001192 Median :0.001192 Median :1.444
## Mean :1 Mean :0.001192 Mean :0.001192 Mean :1.444
## 3rd Qu.:1 3rd Qu.:0.001192 3rd Qu.:0.001192 3rd Qu.:1.444
## Max. :1 Max. :0.001192 Max. :0.001192 Max. :1.444FMM.CPD <- glmer(F.abs.res.CPD ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.CPD ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.CPD.a <- anova(FMM.CPD, test="Chisq")## Warning in anova.merMod(FMM.CPD, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0004551 Min. :0.0004551 Min. :0.929
## 1st Qu.:1 1st Qu.:0.0004551 1st Qu.:0.0004551 1st Qu.:0.929
## Median :1 Median :0.0004551 Median :0.0004551 Median :0.929
## Mean :1 Mean :0.0004551 Mean :0.0004551 Mean :0.929
## 3rd Qu.:1 3rd Qu.:0.0004551 3rd Qu.:0.0004551 3rd Qu.:0.929
## Max. :1 Max. :0.0004551 Max. :0.0004551 Max. :0.929FMM.CPL <- glmer(F.abs.res.CPL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.CPL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.CPL.a <- anova(FMM.CPL, test="Chisq")## Warning in anova.merMod(FMM.CPL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :5.143e-07 Min. :5.143e-07 Min. :0.0007224
## 1st Qu.:1 1st Qu.:5.143e-07 1st Qu.:5.143e-07 1st Qu.:0.0007224
## Median :1 Median :5.143e-07 Median :5.143e-07 Median :0.0007224
## Mean :1 Mean :5.143e-07 Mean :5.143e-07 Mean :0.0007224
## 3rd Qu.:1 3rd Qu.:5.143e-07 3rd Qu.:5.143e-07 3rd Qu.:0.0007224
## Max. :1 Max. :5.143e-07 Max. :5.143e-07 Max. :0.0007224FMM.PreDL <- glmer(F.abs.res.PreDL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.PreDL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM.PreDL.a <- anova(FMM.PreDL, test="Chisq")## Warning in anova.merMod(FMM.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0007427 Min. :0.0007427 Min. :0.5739
## 1st Qu.:1 1st Qu.:0.0007427 1st Qu.:0.0007427 1st Qu.:0.5739
## Median :1 Median :0.0007427 Median :0.0007427 Median :0.5739
## Mean :1 Mean :0.0007427 Mean :0.0007427 Mean :0.5739
## 3rd Qu.:1 3rd Qu.:0.0007427 3rd Qu.:0.0007427 3rd Qu.:0.5739
## Max. :1 Max. :0.0007427 Max. :0.0007427 Max. :0.5739FMM.DbL <- glmer(F.abs.res.DbL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.DbL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.DbL.a <- anova(FMM.DbL, test="Chisq")## Warning in anova.merMod(FMM.DbL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.003626 Min. :0.003626 Min. :4.467
## 1st Qu.:1 1st Qu.:0.003626 1st Qu.:0.003626 1st Qu.:4.467
## Median :1 Median :0.003626 Median :0.003626 Median :4.467
## Mean :1 Mean :0.003626 Mean :0.003626 Mean :4.467
## 3rd Qu.:1 3rd Qu.:0.003626 3rd Qu.:0.003626 3rd Qu.:4.467
## Max. :1 Max. :0.003626 Max. :0.003626 Max. :4.467FMM.HL <- glmer(F.abs.res.HL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.HL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.HL.a <- anova(FMM.HL, test="Chisq")## Warning in anova.merMod(FMM.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :2.563e-06 Min. :2.563e-06 Min. :0.003998
## 1st Qu.:1 1st Qu.:2.563e-06 1st Qu.:2.563e-06 1st Qu.:0.003998
## Median :1 Median :2.563e-06 Median :2.563e-06 Median :0.003998
## Mean :1 Mean :2.563e-06 Mean :2.563e-06 Mean :0.003998
## 3rd Qu.:1 3rd Qu.:2.563e-06 3rd Qu.:2.563e-06 3rd Qu.:0.003998
## Max. :1 Max. :2.563e-06 Max. :2.563e-06 Max. :0.003998FMM.HD <- glmer(F.abs.res.HD ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.HD ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.HD.a <- anova(FMM.HD, test="Chisq")## Warning in anova.merMod(FMM.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0001079 Min. :0.0001079 Min. :0.1894
## 1st Qu.:1 1st Qu.:0.0001079 1st Qu.:0.0001079 1st Qu.:0.1894
## Median :1 Median :0.0001079 Median :0.0001079 Median :0.1894
## Mean :1 Mean :0.0001079 Mean :0.0001079 Mean :0.1894
## 3rd Qu.:1 3rd Qu.:0.0001079 3rd Qu.:0.0001079 3rd Qu.:0.1894
## Max. :1 Max. :0.0001079 Max. :0.0001079 Max. :0.1894FMM.HW <- glmer(F.abs.res.HW ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.HW ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM.HW.a <- anova(FMM.HW, test="Chisq")## Warning in anova.merMod(FMM.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0002723 Min. :0.0002723 Min. :0.5148
## 1st Qu.:1 1st Qu.:0.0002723 1st Qu.:0.0002723 1st Qu.:0.5148
## Median :1 Median :0.0002723 Median :0.0002723 Median :0.5148
## Mean :1 Mean :0.0002723 Mean :0.0002723 Mean :0.5148
## 3rd Qu.:1 3rd Qu.:0.0002723 3rd Qu.:0.0002723 3rd Qu.:0.5148
## Max. :1 Max. :0.0002723 Max. :0.0002723 Max. :0.5148FMM.SnL <- glmer(F.abs.res.SnL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.SnL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.SnL.a <- anova(FMM.SnL, test="Chisq")## Warning in anova.merMod(FMM.SnL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0008833 Min. :0.0008833 Min. :2.043
## 1st Qu.:1 1st Qu.:0.0008833 1st Qu.:0.0008833 1st Qu.:2.043
## Median :1 Median :0.0008833 Median :0.0008833 Median :2.043
## Mean :1 Mean :0.0008833 Mean :0.0008833 Mean :2.043
## 3rd Qu.:1 3rd Qu.:0.0008833 3rd Qu.:0.0008833 3rd Qu.:2.043
## Max. :1 Max. :0.0008833 Max. :0.0008833 Max. :2.043FMM.OL <- glmer(F.abs.res.OL ~ SPP+ (1|QUARTILE), data=Fraw3)## Warning in glmer(F.abs.res.OL ~ SPP + (1 | QUARTILE), data = Fraw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM.OL.a <- anova(FMM.OL, test="Chisq")## Warning in anova.merMod(FMM.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.514e-32 Min. :1.514e-32 Min. :2.251
## 1st Qu.:1 1st Qu.:1.514e-32 1st Qu.:1.514e-32 1st Qu.:2.251
## Median :1 Median :1.514e-32 Median :1.514e-32 Median :2.251
## Mean :1 Mean :1.514e-32 Mean :1.514e-32 Mean :2.251
## 3rd Qu.:1 3rd Qu.:1.514e-32 3rd Qu.:1.514e-32 3rd Qu.:2.251
## Max. :1 Max. :1.514e-32 Max. :1.514e-32 Max. :2.251Watershed nested in Basin
FMM1.D <- glmer(F.abs.res.D ~ SPP + (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.D ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.D.a <- anova(FMM1.D, test="Chisq")## Warning in anova.merMod(FMM1.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.1778 Min. :0.1778 Min. :1.173
## 1st Qu.:1 1st Qu.:0.1778 1st Qu.:0.1778 1st Qu.:1.173
## Median :1 Median :0.1778 Median :0.1778 Median :1.173
## Mean :1 Mean :0.1778 Mean :0.1778 Mean :1.173
## 3rd Qu.:1 3rd Qu.:0.1778 3rd Qu.:0.1778 3rd Qu.:1.173
## Max. :1 Max. :0.1778 Max. :0.1778 Max. :1.173FMM1.P1.R <- glmer(F.abs.res.P1.R ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.P1.R ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.P1.Ra <- anova(FMM1.P1.R, test="Chisq")## Warning in anova.merMod(FMM1.P1.R, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.6331 Min. :0.6331 Min. :3.713
## 1st Qu.:1 1st Qu.:0.6331 1st Qu.:0.6331 1st Qu.:3.713
## Median :1 Median :0.6331 Median :0.6331 Median :3.713
## Mean :1 Mean :0.6331 Mean :0.6331 Mean :3.713
## 3rd Qu.:1 3rd Qu.:0.6331 3rd Qu.:0.6331 3rd Qu.:3.713
## Max. :1 Max. :0.6331 Max. :0.6331 Max. :3.713FMM1.LLSC <- glmer(F.abs.res.LLSC ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.LLSC ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM1.LLSC.a <- anova(FMM1.LLSC, test="Chisq")## Warning in anova.merMod(FMM1.LLSC, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.1297 Min. :0.1297 Min. :0.3171
## 1st Qu.:1 1st Qu.:0.1297 1st Qu.:0.1297 1st Qu.:0.3171
## Median :1 Median :0.1297 Median :0.1297 Median :0.3171
## Mean :1 Mean :0.1297 Mean :0.1297 Mean :0.3171
## 3rd Qu.:1 3rd Qu.:0.1297 3rd Qu.:0.1297 3rd Qu.:0.3171
## Max. :1 Max. :0.1297 Max. :0.1297 Max. :0.3171FMM1.SBLL <- glmer(F.abs.res.SBLL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.SBLL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.SBLL.a <- anova(FMM1.SBLL, test="Chisq")## Warning in anova.merMod(FMM1.SBLL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.01215 Min. :0.01215 Min. :0.09271
## 1st Qu.:1 1st Qu.:0.01215 1st Qu.:0.01215 1st Qu.:0.09271
## Median :1 Median :0.01215 Median :0.01215 Median :0.09271
## Mean :1 Mean :0.01215 Mean :0.01215 Mean :0.09271
## 3rd Qu.:1 3rd Qu.:0.01215 3rd Qu.:0.01215 3rd Qu.:0.09271
## Max. :1 Max. :0.01215 Max. :0.01215 Max. :0.09271FMM1.BD <- glmer(F.abs.res.BD ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.BD ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.BD.a <- anova(FMM1.BD, test="Chisq")## Warning in anova.merMod(FMM1.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001216 Min. :0.001216 Min. :1.487
## 1st Qu.:1 1st Qu.:0.001216 1st Qu.:0.001216 1st Qu.:1.487
## Median :1 Median :0.001216 Median :0.001216 Median :1.487
## Mean :1 Mean :0.001216 Mean :0.001216 Mean :1.487
## 3rd Qu.:1 3rd Qu.:0.001216 3rd Qu.:0.001216 3rd Qu.:1.487
## Max. :1 Max. :0.001216 Max. :0.001216 Max. :1.487FMM1.CPD <- glmer(F.abs.res.CPD ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.CPD ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.CPD.a <- anova(FMM1.CPD, test="Chisq")## Warning in anova.merMod(FMM1.CPD, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0005281 Min. :0.0005281 Min. :1.068
## 1st Qu.:1 1st Qu.:0.0005281 1st Qu.:0.0005281 1st Qu.:1.068
## Median :1 Median :0.0005281 Median :0.0005281 Median :1.068
## Mean :1 Mean :0.0005281 Mean :0.0005281 Mean :1.068
## 3rd Qu.:1 3rd Qu.:0.0005281 3rd Qu.:0.0005281 3rd Qu.:1.068
## Max. :1 Max. :0.0005281 Max. :0.0005281 Max. :1.068FMM1.CPL <- glmer(F.abs.res.CPL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.CPL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM1.CPL.a <- anova(FMM1.CPL, test="Chisq")## Warning in anova.merMod(FMM1.CPL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :5.42e-05 Min. :5.42e-05 Min. :0.07822
## 1st Qu.:1 1st Qu.:5.42e-05 1st Qu.:5.42e-05 1st Qu.:0.07822
## Median :1 Median :5.42e-05 Median :5.42e-05 Median :0.07822
## Mean :1 Mean :5.42e-05 Mean :5.42e-05 Mean :0.07822
## 3rd Qu.:1 3rd Qu.:5.42e-05 3rd Qu.:5.42e-05 3rd Qu.:0.07822
## Max. :1 Max. :5.42e-05 Max. :5.42e-05 Max. :0.07822FMM1.PreDL <- glmer(F.abs.res.PreDL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.PreDL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.PreDL.a <- anova(FMM1.PreDL, test="Chisq")## Warning in anova.merMod(FMM1.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0009603 Min. :0.0009603 Min. :0.7645
## 1st Qu.:1 1st Qu.:0.0009603 1st Qu.:0.0009603 1st Qu.:0.7645
## Median :1 Median :0.0009603 Median :0.0009603 Median :0.7645
## Mean :1 Mean :0.0009603 Mean :0.0009603 Mean :0.7645
## 3rd Qu.:1 3rd Qu.:0.0009603 3rd Qu.:0.0009603 3rd Qu.:0.7645
## Max. :1 Max. :0.0009603 Max. :0.0009603 Max. :0.7645FMM1.DbL <- glmer(F.abs.res.DbL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.DbL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM1.DbL.a <- anova(FMM1.DbL, test="Chisq")## Warning in anova.merMod(FMM1.DbL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.003605 Min. :0.003605 Min. :4.397
## 1st Qu.:1 1st Qu.:0.003605 1st Qu.:0.003605 1st Qu.:4.397
## Median :1 Median :0.003605 Median :0.003605 Median :4.397
## Mean :1 Mean :0.003605 Mean :0.003605 Mean :4.397
## 3rd Qu.:1 3rd Qu.:0.003605 3rd Qu.:0.003605 3rd Qu.:4.397
## Max. :1 Max. :0.003605 Max. :0.003605 Max. :4.397FMM1.HL <- glmer(F.abs.res.HL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.HL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.HL.a <- anova(FMM1.HL, test="Chisq")## Warning in anova.merMod(FMM1.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :7.767e-06 Min. :7.767e-06 Min. :0.01222
## 1st Qu.:1 1st Qu.:7.767e-06 1st Qu.:7.767e-06 1st Qu.:0.01222
## Median :1 Median :7.767e-06 Median :7.767e-06 Median :0.01222
## Mean :1 Mean :7.767e-06 Mean :7.767e-06 Mean :0.01222
## 3rd Qu.:1 3rd Qu.:7.767e-06 3rd Qu.:7.767e-06 3rd Qu.:0.01222
## Max. :1 Max. :7.767e-06 Max. :7.767e-06 Max. :0.01222FMM1.HD <- glmer(F.abs.res.HD ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.HD ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.HD.a <- anova(FMM1.HD, test="Chisq")## Warning in anova.merMod(FMM1.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0001499 Min. :0.0001499 Min. :0.2762
## 1st Qu.:1 1st Qu.:0.0001499 1st Qu.:0.0001499 1st Qu.:0.2762
## Median :1 Median :0.0001499 Median :0.0001499 Median :0.2762
## Mean :1 Mean :0.0001499 Mean :0.0001499 Mean :0.2762
## 3rd Qu.:1 3rd Qu.:0.0001499 3rd Qu.:0.0001499 3rd Qu.:0.2762
## Max. :1 Max. :0.0001499 Max. :0.0001499 Max. :0.2762FMM1.HW <- glmer(F.abs.res.HW ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.HW ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.HW.a <- anova(FMM1.HW, test="Chisq")## Warning in anova.merMod(FMM1.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0002723 Min. :0.0002723 Min. :0.5148
## 1st Qu.:1 1st Qu.:0.0002723 1st Qu.:0.0002723 1st Qu.:0.5148
## Median :1 Median :0.0002723 Median :0.0002723 Median :0.5148
## Mean :1 Mean :0.0002723 Mean :0.0002723 Mean :0.5148
## 3rd Qu.:1 3rd Qu.:0.0002723 3rd Qu.:0.0002723 3rd Qu.:0.5148
## Max. :1 Max. :0.0002723 Max. :0.0002723 Max. :0.5148FMM1.SnL <- glmer(F.abs.res.SnL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.SnL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyFMM1.SnL.a <- anova(FMM1.SnL, test="Chisq")## Warning in anova.merMod(FMM1.SnL, test = "Chisq"): additional arguments
## ignored: 'test'summary(FMM1.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0003644 Min. :0.0003644 Min. :0.8364
## 1st Qu.:1 1st Qu.:0.0003644 1st Qu.:0.0003644 1st Qu.:0.8364
## Median :1 Median :0.0003644 Median :0.0003644 Median :0.8364
## Mean :1 Mean :0.0003644 Mean :0.0003644 Mean :0.8364
## 3rd Qu.:1 3rd Qu.:0.0003644 3rd Qu.:0.0003644 3rd Qu.:0.8364
## Max. :1 Max. :0.0003644 Max. :0.0003644 Max. :0.8364FMM1.OL <- glmer(F.abs.res.OL ~ SPP+ (1|BASIN/WATERSHED), data=Fraw3)## Warning in glmer(F.abs.res.OL ~ SPP + (1 | BASIN/WATERSHED), data = Fraw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')FMM1.OL.a <- anova(FMM1.OL, test="Chisq")## Warning in anova.merMod(FMM1.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(FMM1.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.345e-32 Min. :1.345e-32 Min. :1.994
## 1st Qu.:1 1st Qu.:1.345e-32 1st Qu.:1.345e-32 1st Qu.:1.994
## Median :1 Median :1.345e-32 Median :1.345e-32 Median :1.994
## Mean :1 Mean :1.345e-32 Mean :1.345e-32 Mean :1.994
## 3rd Qu.:1 3rd Qu.:1.345e-32 3rd Qu.:1.345e-32 3rd Qu.:1.994
## Max. :1 Max. :1.345e-32 Max. :1.345e-32 Max. :1.994Levene’s w/ Basin?
Not sure if this is correct, but might try Levene’s test with zone/basin/watershed as an additional independent factor? This is for the traits that did NOT vary with body length.
Zones
library(car)
(FLT2_P2L <- leveneTest(P2.L~SPP*QUARTILE, data=Fraw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 189(FLT2_P2R <- leveneTest(P2.R~SPP*QUARTILE, data=Fraw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 189(FLT2_P1 <- leveneTest(P1~SPP*QUARTILE, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.696 0.1121
## 189(FLT2_A <- leveneTest(A~SPP*QUARTILE, data=Fraw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.1296 0.3462
## 189(FLT2_SALL <- leveneTest(SALL~SPP*QUARTILE, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 8.6118 3.714e-09 ***
## 189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT2_SBLL <- leveneTest(SBLL~SPP*QUARTILE, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.3933 0.2102
## 189(FLT2_SBDF <- leveneTest(SBDF~SPP*QUARTILE, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.8839 0.07421 .
## 189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT2_FLA <- leveneTest(FLA~SPP*QUARTILE, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.7622 0.09713 .
## 189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Basins
(FLT3_P2L <- leveneTest(P2.L~SPP*BASIN, data=Fraw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 NaN NaN
## 188(FLT3_P2R <- leveneTest(P2.R~SPP*BASIN, data=Fraw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 NaN NaN
## 188(FLT3_P1 <- leveneTest(P1~SPP*BASIN, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 1.353 0.2198
## 188(FLT3_A <- leveneTest(A~SPP*BASIN, data=Fraw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 2.3786 0.01834 *
## 188
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT3_SALL <- leveneTest(SALL~SPP*BASIN, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 5.9029 9.638e-07 ***
## 188
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT3_SBLL <- leveneTest(SBLL~SPP*BASIN, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 1.1409 0.3378
## 188(FLT3_SBDF <- leveneTest(SBDF~SPP*BASIN, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 2.9845 0.003588 **
## 188
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT3_FLA <- leveneTest(FLA~SPP*BASIN, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 8 0.5557 0.8131
## 188Watersheds
(FLT4_P2L <- leveneTest(P2.L~SPP*WATERSHED, data=Fraw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 NaN NaN
## 181(FLT4_P2R <- leveneTest(P2.R~SPP*WATERSHED, data=Fraw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 NaN NaN
## 181(FLT4_P1 <- leveneTest(P1~SPP*WATERSHED, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 1.8454 0.03158 *
## 181
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT4_A <- leveneTest(A~SPP*WATERSHED, data=Fraw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 1.2637 0.2294
## 181(FLT4_SALL <- leveneTest(SALL~SPP*WATERSHED, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 5.0755 2.528e-08 ***
## 181
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT4_SBLL <- leveneTest(SBLL~SPP*WATERSHED, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 1.8449 0.03165 *
## 181
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT4_SBDF <- leveneTest(SBDF~SPP*WATERSHED, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 2.2472 0.006442 **
## 181
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(FLT4_FLA <- leveneTest(FLA~SPP*WATERSHED, data=Fraw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 15 1.2278 0.2544
## 181